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+# Complete Handbook (Structured Markdown)
+
+
+
+## Postgraduate Faculty Identity :: Vision and Mission
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 186-186
+
+### Page 186
+To enrich lives and shape the future for the nation and humanity through
+education, research and technopreneurship
+A globally-influential faculty, enriching lives & shaping the future through
+computing technology
+To sustain an outstanding faculty dedicated to excellence in undergraduate and
+postgraduate teaching, learning and research
+To contribute towards the development of the nation through the production of
+quality research and publications
+To provide innovative academic programs that can respond to the changing needs
+of the society
+To produce quality graduates who are equipped with advanced knowledge and
+skills of computer science and information technology
+v i s i o n
+m i s i o n
+O B J E C T I V E S
+
+
+## Faculty Staff :: Dean's Office and Management
+
+- scope_label: general
+- source_doc: Complete Handbook
+- pages: 6-8
+
+### Page 6
+DEAN’S OFFICE
+Associate Prof. Dr. Norisma Idris
+a "PhD (Malaya), M.Sc. (Malaya), B.CS. (Hons) (Malaya)
+Dean
+2 Dr. Ong Sim Ying
+/ PhD (UTM), BComSc (SE) (Malaya)
+Deputy Dean
+(Postgraduate)
+: Professor Dr. Nor Liyana Mohd Shuib
+PhD (Malaya), MIT (UKM), BSc (Computer)(Hons)(UTM)
+Deputy Dean
+(Undergraduate)
+: Associate Prof. Dr. Dr. Saaidal Razzalli Azzuhri
+PhD of Computer Networks (University of
+Queensland), MSc (IT) (Malaysia University of Science
+& Technology), BEng (Telecommunication) (Malaya)
+Deputy Dean
+(Research)
+
+### Page 7
+Deputy Dean
+(Development)
+r
+Deputy Dean
+(Student Affairs)
+HONORARY PROFESSOR
+HEAD OF DEPARTMENT
+Software Engineering
+Associate Prof. Dr. Siti Hafizah Ab. Hamid
+PhD (Malaya), M.Sc (Computer System Design),
+(Manchester University Institute of Science and
+Technology), BSc (Hons) (Computer) (UTM)
+Dr. Erma Rahayu Mohd Faizal Abdullah
+PhD (UTM), Master OITA University (Kejuruteraan
+Elektrik), BComSc (Malaya)
+Honorary Professor Dr. Abdullah Gani
+PhD, University of Sheffield, UK, MSc (Information
+Management, Hull University, UK, 8.Phil, Hull
+University, UK
+Honorary Professor Datin Dr. Sameem Abdul Kareem
+PhD, UM (2002), MCS, Univ. of Wales, UK (1992), BSc,
+UM (1986)
+Dr. Asmiza Abdul Sani
+PhD (University of York, UK), Master (University of
+York, UK), BComSc (SE) (Malaya)
+
+### Page 8
+Axtifical Intelligence
+Computer System
+and Technology
+Information Systems
+Dr. Muhammad Shahreeza Safiruz Kassim
+PhD (Computer Science) (University of Southampton),
+MSc (Al)(Distinction) (University of Southampton, UK)
+‘BEng (Nagaoka University of Technology, Japan)
+Associate Prof. Dr. Amirrudin Kamsin
+PhD (University College London, UK), MSc (NCCA,
+Bournemouth University, UK), BSc (Hons) (Malaya)
+Dr. Hoo Wai Lam
+PhD (UM), 8.CS. (Hons) (UM)
+
+
+## Faculty Staff :: Department of Artificial Intelligence
+
+- scope_label: general
+- source_doc: Complete Handbook
+- pages: 9-12
+
+### Page 9
+DEPARTMENT OF ARTIFICIAL INTELLIGENCE
+Head of Department:
+Dr. Muhammad Shahreeza Safiruz Kassim
+Muhammad
+‘Shahreeza Safiruz
+Kassim
+(0813)
+an
+MSc in Artificial inteligence
+(Distinction), University of
+‘Southampton, UK
+Bachelor of Engineering,
+Nagaoka University of
+Technology, Japan
+esian probabilty modeling
+'* Machine Learning
+‘* Parameter estimation
+Z| Prot it Dr Chan
+‘Chee Seng
+(vK7)
+in
+PhD (2008)
+PhO, University of Portsmouth,
+Master (2008)
+MSc in Communication
+‘Systems Engineering,
+University of Portsmouth, UK.
+Bachelor (2003)
+‘BEng (Hons) in Electronics
+Engineering, Multimedia
+University
++ Fuazy Sels_& Systems and
+Computer Vision (Image/Video
+Content Analysis and Human-
+Robot Interaction)
+3_| Prot Dr Loo Cha
+Kiong
+(vkK6)
+th
+PHD (2004)
+PhO, Universiti Sains Malaysia
+Bachelor (1996)
+Bachelor of Engineering
+(Hons), Universiti Malaya,
+© Soft Computing
+Affective Computing
+‘¢ Human-Robot interaction (HIR)
+© Deep Learning,
+“4_[ Asoo. Prof. Or.
+Norisma Idris
+(0s14)
+ia
+PAO 2077)
+PhD (Natural Language
+Processing), Universiti Malaya,
+Master (2001)
+Master of Computer Science,
+Universiti Malaya.
+Bachelor (1999)
+Bachelor of Computer Science
+(Hons), Universiti Malaya,
+‘ Arificaa intelligence in Education
+(Automated summarization
+‘assessment, Summary sentence
+‘decomposition, Adaptive
+learning, essay grading system)
+Natural Language Processing
+(Text Normalization, Malay text
+processing, Stemming algorithm,
+‘Sentiment Analysis))
+
+### Page 10
+‘Assoc. Prof. Dr. Aznul
+Qalid Md Sabri
+(0s14)
+PAD (2073)
+Doctoral Degree (PhD), Ecole
+Des Mines, Douai, Perancis
+(Kepintaran Buatan)
+Master (2009)
+Masters in Vision and
+Robotics, Heriot-Watt
+University
+Master Degree, (2009)
+Universite De Bourgogne
+(Robotik)
+Bachelor (2006)
+Bachelor of Computer
+‘Science, Universiti Malaya
+‘Computer vision (Human
+‘Action Classification, Feature
+Extraction, Object Detection!
+Recognition, Biometrics,
+Machine ‘Learning, Data
+Analytics)
+Dr. Erma Rahaya
+Mohd Faizal Abdullah
+(0813)
+PAD (2073)
+Doctoral Degree, Universiti
+Teknologi MARA
+(Kejuruteraan Elektrik)
+Master, (2007)
+‘OITA University (Kejuruteraan
+Elektrik)
+Bachelor (2003)
+Bachelor of Computer Science
+(Hons)(Multimedia), Universiti
+Malaya
+‘@ Computer_Vision and Image
+Processing
+*Neural_ Networks, Genetic
+Algorithms and Fuzzy Logic
+(Backpropagation algorithm)
+‘* Pattern Recognition
+Drew Wel Shiung
+(0813)
+PAD (202) (Computer
+‘Science), Universiti Malaya
+Master of Biomedical
+Engineering (2015), Universiti
+Malaya
+Bachelor of Electronics
+Engineering (2010),
+Multimedia University
+‘Affective computing, artificial
+intelligence, evolutionary
+‘computing, neural networks.
+‘Dr, Lim Chee Kau
+(0813)
+PAD (2075)
+PhO (Comp Science),
+Universiti Malaya
+Master (2002)
+Master of Computer, Universiti
+Malaya
+Bachelor (1996)
+Bachelor of Science (Hors),
+Universiti Sains Malaysia
+‘* Fuzzy Relational Theory
+‘¢ Fuzzy Logic
+Dr. Nurul Japar
+(0813)
+PAD (Oz)
+PhD (Computer Vision),
+Universiti Malaya
+Bachelor (2018)
+Bachelor of Computer Science
+(Artificial inteligence),
+Universiti Malaya,
+‘> Image Processing
+‘* Computer Vision
+‘* Machine Learming
+
+### Page 11
+70.
+Dr. Saw Shier Nee
+(0813)
+PAD (2019)
+PhD, National University of
+‘Singapore
+Bachelor (2013)
+Bachelor of Biomedical
+Engineering, Universiti Malaya
+Tin Healtheare
+¢ Health informatics
+‘¢ Machine Learning
+TT
+‘Dr. Unaizah Harum
+‘Obaidellah
+(0813)
+PRO QO
+Cognitive Science, University
+of Sussex, UK
+Master (2007)
+Master of Computer Science
+(Artificial intelligence),
+Universiti Malaya,
+Bachelor (2004)
+Bachelor of Computer Science
+(Artificial inteligence),
+Universiti Malaya
+‘Cognitive Science (Diagrams,
+Semertic and spatial
+representation, Memory,
+Leaming)
+‘*Blomedical simulation &
+‘modeling
+1%
+Dr, Woo Chaw Seng
+(0813)
+PAD (2007)
+PhD, Queensland University of
+Technology, Australia
+Master (1999)
+Master of Computer Science,
+Universiti Malaya.
+Bachelor (1996)
+Bachelor of Computer
+‘Science, Universiti Malaya
+‘© Arificial Neural Network
+© Biomedical image
+‘Segmentation
+© Wavelet Transform
+Applications
+© Data Hiding and
+Steganography (Multimedia
+Watermarking)
+© Mobile Computing (mobile
+security)
+© Soft Computing (Swarm
+Behavior, Software Agent)
+© Security Services Sn: Digital
+Forensic, Steganography,
+Network’ Security, Public Key
+Infrastructure and Biometrics
+(Digital Watermarking)
+‘* National Security Sn: including
+Health Aspects Such as
+Medicine and Medical Supply,
+Disaster Preparedness and
+Imported Diseases (Tele-
+Medicine)
+© Biometrics Security System
+(mobile biometric systems)
+
+### Page 12
+73.
+Dr. Zati Hakim Azizul
+Hasan
+(0813)
+r
+PAD (2074)
+PhD in Artificial nteligenoe
+and Roboties, Auckland
+University of Technology, New
+Zealand
+Master (2007)
+Master of Computer Science
+(Artificial Intelligence),
+Universiti Malaya,
+Bachelor (2004)
+Bachelor of Computer Science
+(Artificial Intelligence),
+Universiti Malaya,
+Robotics (mobile robots,
+localization and mapping)
+‘* Cognitive Mapping _ (spatial
+cognition in humans and
+animals)
+© Biomedical simulation &
+modelling
+Biometrics (Speech processing,
+‘spectral analysis)
+Dr Mohamed NW.
+Lubani
+(0s11)
+da
+PHD (Computer Science) The
+‘National University of Malaysia
+(UKM)
+Master of Computer Science
+University Malaya (UM)
+Bachelor of Information
+Technology
+Damascus University,
+Damascus, Syria
+‘© Arificial inteligence
+‘Machine Learning for Natural
+Language Processing
+3}
+Dr_Uzair Tehtiag
+(0813)
+PhD (Computer Science)
+Universiti Malaya
+Master of Science (Computer
+Science), (Computer Science)
+National University of
+‘Computer and Emerging
+Sciences
+BS in Information
+Technology, (Information
+Technology) Bahauddin
+Zakariya University
+‘* Machine Leaming
+oc
+Dr_ Zainab Malik
+(0813)
+PAD (Arificial
+Intelligence/Computer Vision),
+Universiti Teknologi Malaysia
+(UTM)
+M. Phill (Computer Science),
+(Quad-i-Azam University
+Bachelor of Science in
+‘Computer Science, National
+University of Modern
+Languages
+‘© Arificial nteligence
+‘¢ Computer Vision
+
+
+## Faculty Staff :: Department of Software Engineering
+
+- scope_label: general
+- source_doc: Complete Handbook
+- pages: 13-16
+
+### Page 13
+EPARTMENT OF
+Head of Department:
+Dr. Asmiza Abdul Sani
+r
+smiza Abdul Sant
+(813)
+B’
+Unwerey Yor,
+Master (2007)
+University of York, UK
+Bachelor (2008)
+Bachelor of Computer Science
+(Hons) (Software
+Engineering), Universit
+‘ormal methods,
+Malaya,
+,_| Prof. Dr. Chew Thiam | PD (2009) ‘Web Performance Analysis and
+Kian University of Glasgow, Management (Web Performance)
+(vK7) ‘Scotland
+‘© Usability of Web-Based Systems
+Master (2000) (Web Usability)
+Master of Computer Science,
+Universiti Malaya, + Software Architecture
+(interoperability)
+Bachelor (1998)
+Bachelor of Computer ‘* Personalised and —Community-
+‘Science, Universiti Malaya, Based Healthcare (ICT,
+Healthcare, Interdisciplinary)
+Prof Dr. StiHafizah | PhD (2073) '® Software Verification, Validation &
+‘Ab. Hamid Universiti Malaya, Testing (Test Cases, Formal
+(vK7) Specification)
+Master (2002)
+b
+Master of Science (Computer
+‘System Design), Manchester
+University Institute of Science
+and Technology.
+Bachelor (2000)
+Bachelor of Science (Hons)
+(Computer Science), Universiti
+Teknologi Malaysia, Skudai
+‘* Logics and Meanings of Programs
+(Formal Methods)
+¢ Mathematical Logic and Formal
+Language (Object-Oriented
+Languages (001))
+¢ Edutainment (Mobile Games, E-
+Leaming, ‘Object-Oriented
+Programming)
+‘* Project Management (PRINCE2)
+TT Ass05 FOTO
+Mumtaz Begum Peer
+Mustafa
+(ostay
+Bo
+PAD (2072)
+Universiti Malaya,
+Master (2008)
+Master of Science, Universit!
+Malaya.
+Bachelor (2002)
+Bachelor of Science
+(Computer Science), Universit
+Putra Malaysia
+Diploma (1998)
+Pusat Teknologi dan
+Pengurusan Lanjutan (PTPL),
+Malaysia
+‘Component Based Software
+Development (Component Based
+Software Engineering, Software
+Reuse, Reusable Component)
+‘* Software Testing
+'* Speech Recognition
+‘# Speech Synthesis
+‘* Pattern Recognition
+© Software Agents:
+‘* Human Computer Interaction
+
+### Page 14
+“Assoc Prof Dr. Raja
+Jamilah Raja Yusof
+(0814)
+PnD (2012)
+Universiti Malaya.
+Master (2000)
+Master of Computer Sciense,
+Universiti Nataya
+‘Human Computer Interaction
+(Interface “Design, _ Information
+Visualization, Hierarchical Task
+Analysis Mode!)
+© E-Cultture (Muslim information
+System, _Techno-Daie, Islam,
+Bachelor (1997)
+eal eneena Science and Technology)
+Imperial College ‘© Cognitive Psychology
+Science, Technology and
+science (Reading Comprehension)
+« Information Processing
+(Arabic Stemming)
+‘Information, Computer and
+‘Communication Technology (ICT),
+Software Engineering
+Dr. Adelen Asem PRD of Computer Science ‘ Human Computer Interaction
+Zavareh
+(0813)
+on
+(Artificial Intelligence),
+Universiti Malaya (2014)
+Master of Computer Science,
+University of Pune, India
+(2008)
+Bachelor of Computer
+Science, University of Ashrafi
+Isfahani, Isfahan, tran (2008)
+‘© Evaluation of Software and
+‘Systems
+‘¢ Neuro Fuzzy Inference Systems
+‘* Multi Criteria Decision Analysis
+‘© Software Design
+© Data Analysis
+Big Data
+‘* Decision Support Systems
+‘« Knowledge Based Systems
+© E-Commerce
+Dr_Nazean Jomhant
+(0813)
+ti
+PhD (2010)
+Manchester University, United
+Kingdom
+Master (2001)
+Master of Science, University
+of Essex, Colchester, UK
+Bachelor (2000)
+Bachelor of Science (Hons)
+(Information Science),
+Universiti Kebangsaan
+Malaysia.
+‘ Inferface Design (Order Adult,
+Child, Autistic and Computer)
+Dr_Ong Sim Ying
+(0813)
+i
+PRD (2075),
+Universiti Malaya
+Bachelor (2007)
+Bachelor of Computer Science
+(Software Engineering)
+Universiti Malaya
+‘Image, Signal and Video Coding
+‘and Processing
+« Information Security (Data Hiding
+‘and Encryption)
+‘¢ Linear Programming
+
+### Page 15
+Dr Su Moon Ting ‘PAD (2016) ‘Service-Oriented Architecture)
+(0813) University of Auckland, New
+Zealand ‘© Education (E-Learning)
+Master (1999) © Computer Aided Software
+Master of Science (Computer | Architecture (Software
+pes
+Science), Universiti Putra
+Malaysia,
+Bachelor (1996)
+Bachelor of Computer Science
+(Hons), Universiti Putra
+Malaysia,
+‘Architecture Documentation,
+‘Architectural Knowledge)
+Web Services (Software
+Engineering (Case) Tools
+(Syntax-Directed Programming
+Editor)
+Virtual Reality (Vrml, Vr for
+Internet)
+Web services composition
+# End-user development!
+programming
+70__| Or Hema PAD (2076) * Software _Maintainabilty (Aspect
+Subramaniam PhD (Software Engineering), | Oriented Software Engineering)
+(013) Universiti Putra Malaysia
+(UPM) Counseling System (Counseling
+Application)
+Master (2010)
+Master of Computer Science _| # Project Management (Tools Based
+(Software Engineering), Project Management)
+Univers Industn Selangor
+(UNISEL) * Software Toots (Web
+Development)
+Bachelor (2007)
+BSc (Information Technology),
+Universit Industri Selangor
+(UNISEL)
+77_[ Or Cham Yinka | PRO 20TH) ‘= Software Process Modeling
+(0813) Dootor of Philosophy in
+‘Computer Science & © Software Quality,
+Engineering, The University of
+New SouthWales, Australia |» Requirements Engineering
+Master (2005) © Software Testing
+Master of Science in
+Information Technology, Risk Management
+Malaysia University of Science
+and Technology, Malaysia.
+Bachelor (2003)
+Bachelor of Computer Science
+(Software Engineering),
+Universiti Malaya
+72 [Dr Mohamad Hazim | Dootor of Philosophy (PRD) | « Computer and information security
+Imperial College London,
+United Kingdom
+Master of Computer Science
+(Research) University of
+Malaya
+Bachelor of Computer Science
+(Computer System and
+Networking) University of
+Malaya
+« Artificial inteligence and machine
+learning
+© Data sciences
+
+### Page 16
+3.
+Dr. Nur Nasuha Mohd
+PAD
+Universiti Malaya
+Bachelor of Computer Science
+(Software Engineering), Pass
+‘with Honours (with Distinction),
+(Kejuruteraan Perisian)
+Universiti Malaya (UM)
+eEficient Resource Management
+(cloud)
+‘Large Scale Processing
+Social Network Analysis,
+Prediction)
+(link
+14] Dr_Uzalr rebar Degree of Doctor of + Non: Communicable Diseases
+(0813) Philosophy, (Data Mining) ‘Nursing (Including Diabetes,
+Universiti Malaya (UM) Rheumatology Nursing) Medical
+and Health Sciences, Nursing,
+Master of Science in Software | Nursing Practices
+Engineering, (Kejuruteraan
+Pefisian) University of ‘+ Neural Network for Machine
+Engineering and Technology | ° Learning
+Tanda ‘Applied Science and Technology,
+Information and Communication
+BSC (Software Engineering), | Technology (ict), Artificial
+(Kejuruteraan Persian) Inteligence and Machine Learning
+University of Engineering and
+Technology Taxila ‘* Quality and Accessable Health
+System
+Human and Societal Resilency,
+Basic Human and Social Needs
+15] Or Sit Noriana Jamal [PRO in Human Computer * Software Engineering
+(0813)
+Interaction & Software
+Engineering, Universiti Putra
+Malaysia (UPM)
+Master of Computer Science
+(Software Engineering),
+Universiti Putra Malaysia
+(UPM)
+Bachelor of Computer Science
+(Hons), Management Science
+University
+Software
+Engineering
+Requirement
+¢ Human-Computer interaction
+‘Interaction Design
+eUlUx
+‘¢ System Analysis & Design
+*Qbject Oriented Software
+Engineering
+‘© Multimedia Computing
+‘¢ Mobile Application Development
+*E-commerce
+© Artificial intelligence
+
+
+## Faculty Staff :: Department of Information Systems
+
+- scope_label: general
+- source_doc: Complete Handbook
+- pages: 17-20
+
+### Page 17
+DEPARTMENT OF INFORMATION SYSTEMS
+Head of Department:
+Dr. Hoo Wai Lam
+‘Dr. Hoo Wai Lam
+(0813)
+ri
+PRD (2075),
+Universiti Malaya (UM)
+Bachelor (2010)
+Bachelor of Computer Science
+(Hons) (2010),
+Universiti Malaya (UM)
+ata Analytics
+© Machine Leaming
+© Computer Vision
+« Attficial Intelligence
+Z| Prof Dr The ving | PHD (2004) = Data Mining
+Wah Universiti Malaya
+(v&7) # Database
+Master (1995)
+Master of Computer Science,
+‘Oklahoma City University,
+USA
+Bachelor (1994)
+Bachelor of Computer
+‘Science, Okiahoma City
+University, USA
+&_| Prof Or Nor Liyana | PRD (2073) * Management Information System
+Mohd Shuib University Malaya (Decision Support System, Expert
+(vk?) System)
+Master (2008)
+Master of Information '* Information Management
+Technol (Ostabase, Data Mining,
+Universiti Kebangsaan information Retrieval
+y Malaysia (UKM) Recommender System, Social
+Media)
+Bachelor (2005)
+Bachelor of Science ‘© Mobile Computing
+(Computer)(Hons), Universiti
+‘Teknolog Malaysia, Skudai | Educational Technology _ and
+Media (E-learning, Learning Style,
+Personalization, Information
+Seeking, Social Media)
+4__| Prof. Ts. Dr vimala
+Balakrishnan
+(v7)
+PHD (2008)
+Universiti Multimedia Malaysia
+Master (2002)
+Master of Science (Computer
+Science), Universiti Sains
+Malaysia
+Bachelor (1998)
+Bachelor of Computer Science
+(Hons), Universiti Sains
+Malaysia
+‘* Data and Knowledge Engineering
+(Data Mining, Opinion Mining),
+* Information Retrieval
+Social Media
+‘* Recommender Systems
+
+### Page 18
+‘Assoc. Prof. Ts. Dr. St
+Devi Ravana
+(0814)
+——ee-——
+PhD (2012)
+University of Melbourne,
+Australia,
+Master (2001)
+Master of Software
+Engineering, Universit
+Malaya,
+Bachelor (2000)
+Bachelor of information
+Technology (Hons.)
+(Information Science),
+Universiti Kebangsaan
+Malaysia
+‘Search Engine (IR Evaluation (e.g
+evaluation metrics, aggregation
+‘methods, experiments)
+‘* Web Application and Services
+‘Assoc. Prof. Dr,
+Maizatul Akmar Ismail
+(0s14)
+PRD (2071)
+Universiti Malaya,
+Master (2002)
+Master of Science, Universit
+Putra Malaysia
+Bachelor (1999)
+Bachelor of Information
+Technology, Universiti Malaya
+‘ Management Information System,
+Semantic Web in Education,
+Knowledge Management, E-
+Commerce.
+Assoo. Prof Dr PRO OTS) sTafomnation Senses Te"
+‘Sureya Hamid Gompuing ena formation |” Government, e-Leaning, &
+(ost) Systems, The Unwersiy of | commerce, oybersecurty
+2 Melbourne, Austral awareness and Is for
+we Sustainability
+Master (2002)
+Master of Information
+Technology, Universiti
+Kebangsaan Malaysia,
+Bachelor (1998)
+Bachelor of Information
+Technology (Hons. In
+Industrial Computing),
+Universiti Kebangsaan
+Malaysia
+ICT and Emergent Information
+Technology (Information Seeking,
+Online Behaviour and Its Impact,
+Activity Theory, Qualitative
+Research and Social Media)
+‘Assoc. Prof_ Dr
+Kasturi Dewi Varathan
+(0814)
+PRD (2072)
+Universiti Kebangsaan
+Malaysia.
+Master (2005)
+Master of Computer Science,
+Universiti Malaya
+Bachelor (2002)
+Bachelor of Information
+Technology (Hons), Universit
+Tenaga Nasional
+Big Data
+« Information Retrieval
+‘© Data Storage and Representations.
+
+### Page 19
+‘Asoo. Prof. Dr. Azah_| PhD (2014) Management Information System
+‘Ani Norman Universiti Malay (Electronic Commerce Security,
+(0s14) Information Security Management,
+Master (2004) Information Systems)
+Master of Information Security,
+Royal Holloway University of
+London, UK
+Bachelor (2000)
+Bachelor of Information
+Technology, Universiti
+Kebangsaan Malaysia
+PRO(UTHM)(2010), (Computer | * Symbolic and ‘Algebraic
+Science) Manipulation
+Universiti Tun Hussein Onn
+(Uthm)
+M.So(Math)(University Gadjah
+‘© Orthogonal Latin Squares, Magic
+‘Squares, And Magic Cubes
+Mada)(2006), (Mathematical _| « Disorete Mathematics,
+Sciences)
+Universiti Gadjan Mada, ‘* Rough Set and Soft Set Theories
+Indonesia
+‘* Decision Support System
+B.Ed(Ahmad Dahian
+University)(2002), (Education) | # Data Mining, Kdd, Soft Computing
+Universitas Ahmad Dahlan
+TH] Ass06. PROF Or PAD OTS = Database (Database Security &
+'Notihan Abdul Ghani | Universiti Teknotogi Malaysia. | Privacy)
+(osi4) Bachelor (2000)
+‘* Digital Image Processing System
+Master (2002) (Image Retrieval)
+{ Master of information
+{ Technology (The Science),
+e Universit: Kebangsaan Data Security (Information
+Malaysia ‘Security and Privacy)
+Bachelor
+Bachelor of information
+Technology, Universiti Utara
+Malaysia.
+Z| Dr Riyaz Apamed | PAD (2079) ‘> Machine Learning
+Ariyaluran Habeeb
+Mohamed Master of Software Data Science
+(S13) Engineering (2013)
+* Generative Al
+B.Eng, (Computer Science
+and Engineering) (2008) ‘* Cloud Computing
+
+### Page 20
+"3. | Ts. Dr. Mohd Shahrul
+Nizam Mohd Danun
+(os13)
+PAD of Information
+Management a
+UiTM
+Master's ‘in Intellectual
+Property, UKM
+BSc. Degree in Computer
+‘Science (Hons), USM
+‘* Information Systems
+'* Big Data & Data Science
+‘¢ Internet of Things (loT)
+'* Cloud Computing
+
+
+## Postgraduate General Information :: Legislation and Prescribed Rules
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 126-126
+
+### Page 126
+LEGISLATION
+& PRESCRIBED RULES
+(1) Master’s Programmes
+Master's candidates are governed by the Universiti Malaya (Master's Degree)
+Rules and Regulations, 2019.
+(2) Ph.D Programme
+Ph.D candidates are governed by the Universiti Malaya (Degree of Doctor of
+Philosophy) Rules and Regulations, 2019. In addition to the above, all
+postgraduate candidates are also governed by the Universities and University
+Colleges Act, 1971 Constitution of the Universiti Malaya, and all other statutes,
+rules and regulations currently applicable in the University including the Universiti
+Malaya (Discipline of Candidates) Rules 1999.
+The full texts of the above rules and regulations are available at
+https://umsitsquide.um.edumy. As registered candidates of the Universiti
+Malaya, the candidates have the responsibility to be aware of and abide by the
+rules and regulations of the University, the policies and requirements of their
+respective faculties, and the advice contained in this handbook.
+
+
+## Postgraduate General Information :: Marking Scheme and Grade Point Average (GPA)
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 127-127
+
+### Page 127
+MARKING SCHEME AND GRADE
+POINT AVERAGE (GPA)
+The assessment for the examination of the coursework component is based on the
+following marking scheme:
+90.00 - 100.00 At 4.00 HIGH DISTINCTION
+80.00 - 89.99 A 7.00
+75.00 - 79.99 A 3.70 DISTINCTION
+70.00 - 74.99 Bt 3.30
+65.00 - 69.99 B 3.00 PARS
+60.00 - 64.99 B- 2.70
+55.00 - 59.99 c+ 2.30
+50.00 - 54.99 c 2.00
+45.00 - 49.99 Gs 1.70 FAIL
+40.00 - 44.99 D+ 1.50
+36.00 - 39.99 D 4.00
+0.00 - 34.99 F 0.00
+
+
+## Research Guidance :: Progress Report
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 129-129
+
+### Page 129
+PROGRESS REPORT
+All postgraduate research candidates are to submit a progress report online at the
+end of each semester as stipulated. The supervisor shall evaluate the progress
+report and submit the progress report to the Deputy Dean of Higher Degree/Head of
+Department. A candidate whose progress is satisfactory will be recommended for
+continuous of his/her candidature.
+The Faculty shall terminate the candidature of a candidate whose progress is not
+satisfactory for TWO consecutive semesters. A candidate who fails to submit his
+progress report within the stipulated period shall be barred from registering for the
+following semester.
+
+
+## Research Guidance :: Supervision Policy for Postgraduate Programmes
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 130-137
+
+### Page 130
+SUPERVISION POLICY FOR
+POSTGRADUATE PROGRAMMES
+Purpose
+This policy was created with the following objectives:
+(1)
+(2)
+(3)
+(4)
+To explain the criteria for the appointment of the supervisor and the
+role and responsibilities of the supervisor to the candidate in the
+research mode and the coursework and research modes.
+To assist the Responsibility Centre (RC) in making plans for the
+infrastructure, the workload of the academic staff and intake of
+candidates.
+To ensure the quality of supervision is assured and that the research
+produced by the candidate is consistent with the mission and vision of
+the University.
+As a guide for academic staff and candidates in the Universiti
+Malaya in executing the responsibilities as a supervisor and research
+candidate.
+Appointment of Supervisor
+The appointment of a supervisor must meet the following criteria:
+(1)
+(2)
+(3)
+(4)
+It is encouraged to appoint at least two (2) supervisors for each
+candidate. If only one supervisor is appointed, the supervisor must
+have the experience of supervising until graduation at least two (2)
+candidates.
+The appointed supervisor must have a minimum qualification
+equivalent to the degree or at par with the program registered by the
+candidate.
+If the supervisor does not have the qualification stated, experience in
+the research field or related industry can be considered as the criteria
+for appointment as a Supervisor.
+The appointment of a Supervisor shall take into account the research
+skills and experiences which are consistent with the research field of
+the candidate.
+
+### Page 131
+(8)
+(6)
+(7)
+(8)
+(9)
+(10)
+(11)
+(12)
+(13)
+(14)
+Supervisors suggested by prospective candidates, are given priority to
+supervise, except in cases where the RC feels that other supervisors are
+more qualified to supervise.
+Academic staff on sabbatical leave may be allowed to supervise until the
+end of the leave, provided the leave does not affect the candidate's
+supervision. However, based on some specific reasons, the Supervisor may
+apply to not supervise the candidate while on leave and the decision is
+based on the discretion of the relevant RC.
+For academic staff who will be coming to the end of their services, the RC
+should ensure that a replacement supervisor is ap
+months prior to the end of the service date of the
+inted at least six (6)
+I supervisor so that
+both of them can co-supervise without affecting the progress of the
+candidate's research.
+For academic staff have left the service in Universiti Malaya but is still doing
+academic work elsewhere, they may be appointed as co- supervisor and the
+number of candidates supervised shall be limited to five (5) persons, where
+the candidates must be in their final stage of their studies.
+Appointment of an external party (either academic or non-academic) as co-
+supervisors can be considered if the external party is able provide research
+facilities and the expertise which will in turn assist the candidates in their
+research.
+Academic staff should attend training programs
+in supervision or
+enhancement courses prescribed by the Universiti Malaya.
+If the RC would like to appoint a supervisor who is not in compliance with all
+the criteria of appointment specified in the policy, the RC shall submit a letter
+of application together with a strong justification to the Dean of Graduate
+Studies Institute of Graduate Studies for consideration and approval.
+Appointment of supervisors shall be managed by the RC in compliance with
+all the criteria specified in this policy. Appointment made shall take into
+account the space, resources and expertise to support and assist
+candidates, with their research.
+If the appointment of a new supervisor is required for some reason, the
+appointment shall be made according to merit and this case is considered
+as a special case. This case cannot be referred to and be an example or a
+precedent for a case to come.
+In the event of problems of supervision between supervisor and candidate,
+the RC should address this problem. If the problem cannot be resolved, the
+matter may be submitted to the Dean, Institute of Graduate Studies for
+further action.
+Om
+
+### Page 132
+3.
+Ratio between Supervisor and Candidate
+(ty
+2)
+@)
+The maximum ratio for candidates to obtain quality supervision are as,
+follows: -
+Research Fellow 1:3
+Lecturer 1:5
+Senior Lecturer 1:7
+Associate Professor 1:10
+Jusa C Professor 1:15
+Jusa B Professor 1:20
+Jusa A Professor 1:25
+RC may approve a higher maximum number of candidates provided that
+‘supervisor has shown excellent supervision performance.
+RC can also set a different maximum number of students from above to
+meet the requirements of relevant professional bodies.
+In calculating the supervisory workload, three (3) candidates of the
+mixed-mode is equal to two (2) candidates of the research mode.
+Change of Supervisor
+‘Change of supervisor can be implemented as follows:
+(1) If there is strong justification and excuse, the candidate may apply to
+change the supervisor, not more than once during the period of candidature.
+(2) If there is a supervisor who did not perform the supervisory duties
+satisfactorily, the Dean of the RC may appoint any other qualified academic
+staff to replace the said supervisor.
+Family Links
+(1) Supervisors appointed shall not have a close family link to the
+candidate.
+2) Both the appointed supervisors also must not have any family
+relationship with each other.
+
+### Page 133
+Role and Responsibilities of the Supervisor
+The appointed supervisor shall exercise his/her role and responsibilities as set out
+in Appendix A.
+Role and Responsibilities of the Candidate
+The candidate shall also be responsible for the candidature and research
+throughout their status as a student in the Universiti Malaya as set out in Appendix B.
+
+### Page 134
+ROLE AND RESPONSIBILITIES OF THE SUPERVISOR
+Before starting, the supervisor to the candidate will need to know the latest
+university rules and regulations relating to higher degree programs.
+Supervisors should have adequate knowedge, enhanced theoretical and
+conceptual framework, and is up to date in the field of research of the candidate.
+Supervisors should be knowledgeable about the work schedule provided for the
+completion of a research project so that it complies with the provisions of certain
+degrees. This is to ensure the smooth running of the candidate's research project.
+Supervisors are responsible for providing relevant and adequate guidance and
+academic support to students during the supervision period to enable the
+candidate to carry out excellent research and writing. This responsibility includes
+guiding the careful planning of the research, the background and library research,
+the need to attend courses to complete the research, including scientific methods.
+Awareness about the impact of fraud and plagiarism should be informed to the
+candidate.
+Supervisors should interact with the candidate at least two (2) times per month in
+the first semester and once (1) a month for the next semester. For the first
+meeting, the supervisor and the candidate must talk face to face, while, the next
+meeting may be conducted via other methods such as on- line.
+Supervisors are responsible to ensure that candidates could communicate with
+relevant experts should the research area requires so. In certain cases, an
+additional supervisor or consultant may be appointed
+Each supervisor should be appointed to the candidates should know their
+responsibilities respectively and explained to the candidates on the aspects that
+will be monitored. In the event that two (2) supervisors were appointed for each
+candidate, the effective working relationship between all parties needs to be
+maintained together.
+Supervisors need to help candidates in the preparation with regards to the
+presentation at conferences, seminars, meetings and workshops.
+Supervisors are encouraged to record every meeting and discussion with the
+candidate about the study and research of the candidate by providing
+and updating the file on record of achievement and progress of research projects
+for each candidate.
+
+### Page 135
+Supervisors should evaluate the progress of the candidates by getting a written
+report and monitor the performance in a relative manner according to the quality
+set for a certain degree. Candidates should be informed if the quality of her work
+did not reach the required standard. If progress of the candidates is not
+‘satisfactory, the supervisor must take action to help the candidates improve their
+performance. Progress report for each semester for each candidate must be
+submitted by the supervisor to the Academic / Faculty / Institute / Centre as
+scheduled.
+Supervisors should help candidates in academic writing, presentations in
+conferences and submitted for publication. For all the academic papers submitted
+for publication, written jointly by the supervisor and candidate, both have to agree
+to publish them together.
+Supervisors need to help manage and secure any funds (example: Vote PPP,
+UMRG etc.) for research projects.
+Supervisors must ensure work safety rules are followed during the research and
+are carried out in accordance with health and safety ethics policy specified by the
+University.
+Supervisors should provide constructive and critical comments on the candidate's
+drafts of the thesis within a reasonable time and advise the candidate regarding
+the format of the thesis as specified by the University.
+Supervisors should suggest and advise the Post Graduate Office of the RC in the
+process of nomination and evaluation of expertise of internal and external
+examiner. The supervisors also need to ensure that there are no delays in the
+process.
+The Role of Supervisor in the Board of Examiners
+4.
+The role of supervisor in the Board of Examiners is as the advisor. The supervisor
+is not involved in any discussions relating to the results of work submitted by the
+candidate. The supervisor does not function as an examiner.
+The supervisor's attendance in the Board of Examiners shall be by
+invitation only.
+Supervisors are expected to provide supervision reports in the required format
+within a specified time to the Post Graduate Office for the Board of Examiners
+meeting.
+The supervisor should also help the candidates on the corrections to be done
+based on the comments raised by the Board of Examiners and
+continue to oversee the candidate in cases where the thesis is referred back
+for further study.
+Om
+
+### Page 136
+ROLE AND RESPONSIBILITIES OF THE CANDIDATE
+1. Candidates should understand and fulfil all of the conditions contained in the
+letter of offer, rules and regulations applicable to the program. Examples are as
+follows:
+(A) Book of the Universiti Malaya (Master's Degree)
+Regulations 2010 and the Universiti Malaya (Master's
+Degree) 2010;
+(B) Book of the Universiti Malaya (Degree of Doctor of
+Philosophy) 2007 and Regulations of the Universiti Malaya
+(Degree of doctor of Philosophy 2007);
+(c) Program handbook, and
+(D) Postgraduate Handbook.
+2. Candidates should interact with the supervisor at least two (2) times per month in
+the first semester and once (1) a month the next semester. For the first meeting,
+the candidate and supervisor should talk face to face, while, the next meeting can
+be conducted via other methods such as online.
+3. Candidates shall record meetings and discussions on their research each time
+they meet with the supervisor.
+4. Candidates should have a good working relationship with the supervisor.
+5. Candidates must plan the project schedule and comply with the maximum period
+of study.
+6. Candidates should discuss and agree with the supervisor on consultation times.
+7. Candidates must submit progress as specified without falsifying the research
+outcome and is free of plagiarism.
+8. Candidates must notify their supervisor of any problems that may interfere with
+the research.
+9. Candidates shall engage in academic activities organized by the department or
+the RC.
+10. Candidates must plan and ensure sufficient time to do the research and write the
+thesis.
+mm
+
+### Page 137
+11.
+12.
+13.
+14.
+Candidates should ensure that their candidature is always active by
+renewing their registration each semester.
+A candidate shall give three months’ notice to the supervisor or inform the
+supervisor the date for submission of the thesis for examination purposes, so
+there is no delay in the appointment of examiners.
+Candidates are solely responsible for the content, the presentation of thesis
+and viva-voce presentation.
+Candidates are responsible for ensuring that corrections are made in a given
+period after the Board of Examiner's meeting / viva-voce and the Senate.
+
+
+## Research Guidance :: Thesis Preparation Guidelines
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 138-171
+
+### Page 138
+THESIS PREPARATION
+GUIDELINES
+PREFACE
+In the process of completing a postgraduate programme and being awarded the
+degree by the Universiti Malaya, a candidate may be required to submit a research report or
+dissertation or thesis, depending on the requirements of the specific programme.
+The terms “research report’, “dissertation” and “thesis” are defined as follows:
+«Research Report refers to the documentation of research prepared and submitted by the
+candidate for the award of a Master's degree by Coursework or Master's Degree by
+Clinical which may include research paper, research project, project paper, project report
+and research outcome concerned known by whatsoever name;
+* Dissertation refers to the documentation of the original research prepared and submitted
+by the candidate for the award of a Master's degree by Research, and Master's Degree
+by Mixed Mode as well as Doctoral degree by Coursework and Doctoral degree by Clinical;
+Thesis refers to the documentation of the original research prepared and submitted by the
+candidate for the award of a Doctoral degree by Research and Doctoral degree by Mixed
+Mode.
+This guideline will assist the candidates to meet the minimum format requirements set
+by the University to complete the final form of a research report, dissertation or thesis.
+However, the format may differ in each individual Academy/Faculty/Institute/Centre with its
+‘own additional requirements. In this guideline, the term ‘faculty’ will be used to refer to
+Academy/Faculty/Institute/Centre.
+
+### Page 139
+CHAPTER 1: FORMAT OF WRITING
+A research report, dissertation or thesis can be written in one of the following formats:
+* Conventional format;
+* Article style format;
++ Format of published papers (this option is only available for Doctoral programme by
+research candidates)
+These formats serve as a generic guideline for the postgraduate candidates in writing a
+research report, dissertation or thesis. Minor variation of the format as recommended by the
+faculty is allowed. Candidates are advised to discuss with their supervisors to determine which
+format is best suited for the nature of their research work.
+1.1. Conventional Format
+The conventional format follows the traditional monograph structure (Table 1.1). This is the
+most common form of research report/dissertation/thesis used by the candidates.
+Table 1.1: The general structure that follows the conventional format
+Preliminary
+* Title Page
++ Original Literary Work Declaration
+* Abstract
++ Abstrak
++ Acknowledgements
+* Table of Contents
++ List of Figures
+* List of Tables
+«List of Symbols and Abbreviations
++ List of Appendices
+Main Body
++ Chapter 1: Introduction
++ Chapter 2: Literature Review
+* Chapter 3: Methodology
+= Chapter 4: Results
++ Chapter 5: Discussion
++ Chapter 6: Conclusion
++ References (A consolidated list of references for all chapters)
+Supplementary
++ _ List of Publications and Papers Presented
+= Appendix
+
+### Page 140
+1.2 Article Style Format
+Apart from the conventional style of writing, a research report/dissertation/thesis can also be
+presented in the chapters that are in the format of journal article (Table 1.2). The number of
+chapters to be included is at the discretion of the author, depending on the suitability of the
+chapters in answering the research questions.
+This format is also applicable to candidates of Doctoral Degree by Research using Concurrent
+or Prospective Publication. The candidate submits a thesis/conspectus' which incorporates
+publications that may have multiple authors since registration. The candidate may also
+present a portfolio of interconnected, published research papers or articles encapsulated in a
+coherent thesis/conspectus, demonstrating overall an original contribution to knowledge.
+Such publications may include papers, chapters, monographs, books, scholarly editions of a
+text, technical reports, creative work in relevant areas, or other artefacts. The thesis (with the
+publications or equivalent works) must meet the criteria and outcomes established for a
+doctoral award and assessed through a viva voce.
+The article style format should not be confused with the format for thesis by retrospective or
+prior publication. Similar to the conventional format, a research report/dissertation/thesis in
+the article style format should be written extensively to elucidate the different aspects of the
+research work in great details.
+The main body of a research report/dissertation/thesis in the article style format should contain
+the following chapters:
+(a) General Introduction
+The General Introduction gives an overview of the research by outlining the objectives,
+novelty as well as the research questions addressed. This chapter should also explain the
+correlation among the articles/chapters.
+Literature Review
+The Literature Review provides extensive background information on past studies and
+current knowledge pertaining to the research topic.
+(b)
+Article 1, Article 2, Article 3 or more
+Each article should address a specific research objective or a related topic of the study.
+Each article forms a separate chapter and must be written in a cohesive manner with a
+logical and coordinated progression from one article/chapter to the other. The
+article/chapter should consist of its own sections on Introduction, brief Literature Review,
+Methodology, Results, Discussion and Conclusion.
+(c)
+(d) Conclusion and Recommendation
+The Conclusion chapter summarizes the findings in all articles and suggests the future
+direction for research.
+The format specifications of the research report/dissertation/thesis must conform to the
+general research report /dissertation/thesis requirements as outlined in Chapter 2.
+" A critical review which locates the artefact/s within a coherent theoretical framework and field/s of study.
+
+### Page 141
+Table 1.2: The general structure that follows the article style format
+Preliminary
+Title Page
+Original Literary Work Declaration
+Abstract
+Abstrak
+‘Acknowledgements
+Table of Contents
+List of Figures
+List of Tables
+List of Symbols and Abbreviations
+List of Appendices
+Main Body
+Chapter 1: General Introduction
+Chapter 2: Literature Review
+Chapter 3: Article 1*
+3.1 Introduction
+3.2 Literature Review
+3.3 Methodology
+3.4 Results
+3.5 Discussion
+3.6 Conclusion
+Chapter 4: Article 2*
+4.1 Introduction
+4.2 Literature Review
+4.3 Methodology
+44 Results
+4.5 Discussion
+4.6 Conclusion
+Chapter 5: Article 3*
+5.1 Introduction
+5.2 Literature Review
+5.3 Methodology
+5.4 Results
+5.5 Discussion
+5.6 Conclusion
+Chapter 6: Conclusion
+References (A consolidated list of references for all chapters)
+
+### Page 142
+Note:
+*Article is written with a specific title which normally refers to the research
+done
+Supplementary
++ List of Publications and Papers Presented
++ Appendices
++ Co-authors Consent
+1.3. Format of Published Papers
+The University also permits the presentation of thesis for the programme of Doctoral Degree
+by Research i.e. Doctor of Philosophy (PhD) in the format of published and/or submitted
+papers, where such papers have been published or accepted by high impact journals (e.g.
+journals indexed by Web of Science), monographs, books, research-based chapters in books
+and non-traditional research output [NTRO] such as electronic publications, policy paper,
+creative works, artefacts, performance and exhibitions in the field, before or during the period
+of candidature (Table 1.3).
+Papers submitted as a PhD thesis must be based on a particular theme or focus and form a
+cohesive research write up. The quality of a thesis by published papers should be in accordance
+with PhD-level research and must meet the criteria and outcomes established for a doctoral
+award. The following aspects should be taken into consideration before opting for this format
+of writing:
+(a) Type of Publications
+The thesis may comprise published papers and/or manuscripts accepted for publication
+by high impact journals (e.g. journals indexed by Web of Science), monographs, books,
+research-based chapters in books and non-traditional research output [NTRO] such as
+electronic publications, policy paper, creative works, artefacts, performance and
+exhibitions in the field which have not been used to obtain other awards or deemed a part
+of those awards.
+(b) Number of Publications
+For candidates under the programme of Doctoral Degree by Retrospective or Prior
+Publication, the minimum number of publications or equivalent productions is at least five
+(5) and these works must be those published retrospectively within a period not exceeding
+10 years from the date of application. However, in some disciplines where a larger number
+of papers is required to meet the expectations of scope and quality in accordance with
+PhD-level research, the faculty may specify accordingly.
+(c
+Authorship
+Where the papers have more than one author, the candidate must be the first author or
+creator of five (5) of the published works or equivalent productions submitted with the
+contributions of others clearly defined.
+(a) Co-authors Consent
+Candidates must obtain the consent from other co-authors for all papers and/or
+manuscripts and/or publications or equivalent production used as part of their PhD thesis.
+ic)
+
+### Page 143
+The consent can be in the form of a verification from the journal publisher or letter or email
+communication with the co-authors.
+(e) Structure of Thesis
+The thesis in the format of published papers shall consist of the following:
+An abstract, which summarises the most important findings presented in each
+published paper or accepted manuscript or equivalent production. It should indicate
+how the included works are thematically linked or tied to a particular research
+framework and how, when considered together, they contribute significantly to
+knowledge in the discipline.
+The Introduction chapter should include the following:
+"= description of research problem investigated;
+= objectives of the study;
+* list of publications and/or accepted manuscripts or production;
+= the account of research progress linking the publications.
+The account of research progress must link together the various papers or
+production submitted as part of the thesis so that the reader can understand the
+logic behind the progression of the research programme.
+The Literature Review chapter must contain, in accordance with the relevant
+discipline’s norms, a critical review of relevant literature, identify the knowledge gaps
+and the relationship of the literature to the area of research.
+The Methodology chapter (where applicable).
+The core chapter of the thesis consist of the published papers or accepted
+manuscripts or production in their original publication format and should NOT be
+retyped or reformatted. They must be presented coherently in the thesis according
+to the requirement of the University of Malaya (Doctoral Degree) Regulations (latest
+version), including any accompanying declarations. The following must be indicated
+for any jointly written paper:
+= Acknowledgment of co-authors and verification of originality.
+= Aclear statement of the contribution made by each author in any joint published
+work or equivalent production. For example, a statement of contribution from a
+3-author academic research publication is as follows:
+Tang, J.M.Y., Adli, D.S.H., & Belabut, D. (2011). Histological development
+of selected neural structures of Dark-sided Chorus Frog,
+
+### Page 144
+Microhyla heymonsi (Amphibia: Anura). Malaysian Journal of Science,
+29(1), 11-18.
+Tang, J.M.Y. participated in all experiments, coordinated the data analysis
+and contributed to the writing of the manuscript. Adli, D.S.H. supervised
+the development of work and edited the manuscript. Belabut, D. gave
+technical support and conceptual advice, and helped in data
+interpretation.
+() The Discussion chapter explains the cumulative effect of the papers, the
+significance of the findings and the knowledge claimed in the thesis.
+(a The Conclusion summarizes the findings in all published works or equivalent
+production and suggests the future direction for research.
+“ The References chapter lists all works and sources that are cited in the Introduction,
+Literature Review and Conclusion chapters.
+In general, the examination process for theses in the format of published papers is similar to
+that of conventional theses. However the aspects of thesis being evaluated by the examiners
+may slightly differ.
+Candidates under the programme of Doctoral Degree by Retrospective or Prior
+Publication are required to refer to the associated guidelines available.
+
+### Page 145
+Table 1.3: The general structure that follows the format of published papers
+Preliminary
+Title Page
+Original Literary Work Declaration
+Abstract
+Abstrak
+‘Acknowledgements
+Table of Contents
+List of Figures
+List of Tables
+List of Symbols and Abbreviations
+List of Appendices
+Main Body
+Chapter 1: Introduction
+Chapter 2: Literature Review
+Chapter lethodology (where applicable)
+Chapter 4: *Published Paper 1
+“Published Paper 2
+*Published Paper 3 and so on
+“Note: Authors’ contributions must be indicated for each published paper
+References (List of references for chapters of Introduction, Literature Review
+and Conclusion)
+Supplementary
+List of Publications and Papers Presented
+Appendices
+Co-authors Consent
+
+### Page 146
+CHAPTER 2: SEQUENCE OF CONTENTS
+The structure of the research report, dissertation or thesis is based on a standard format which
+contains the three main sections; Preliminary, Main Body and Supplementary.
+241 Preliminary
+This section consists in order of the following:
++ Title Page
++ Original Literary Work Declaration Form
++ Abstract
+» Abstrak
++ Acknowledgements
++ Table of Contents
++ List of Figures
++ List of Tables
++ List of Symbols and Abbreviations
++ List of Appendices
+2.1.1
+Title Page
+The title page is the first page after the front cover and should include:
+(@ The final research title which has been approved by the faculty;
+(0) Name of candidate according to the registration records;
+(© Astatement according to the mode of programme (Table 2.1); and
+(@ The year of submission.
+Table 2.1: Statement on Title Page according to mode of programme
+Master's
+THE REQUIREMENTS FOR
+THE DEGREE OF (Name
+of Programme)
+DEGREE OF (Name
+of Programme)
+Degree
+Research report Dissertation (by Dissertation
+(by Coursework Mixed mode) (by Research)
+or by Clinical)
+RESEARCH REPORT DISSERTATION DISSERTATION
+SUBMITTED TO THE SUBMITTED IN PARTIAL SUBMITTED IN
+(name of the Faculty) FULFILMENT OF THE FULFILMENT OF THE
+UNIVERSITI MALAYA, IN REQUIREMENTS FOR REQUIREMENTS FOR
+PARTIAL FULFILMENT OF THE THE
+DEGREE OF (Name
+of Programme)
+Doctoral
+Degree
+Dissertation (by Coursework Thesis Thesis (by
+or by Clinical) (by Mixed mode) Research)
+DISSERTATION SUBMITTED | THESIS SUBMITTED IN | THESIS SUBMITTED IN
+IN PARTIAL FULFILMENT OF | PARTIAL FULFILMENT OF | — FULFILMENT OF THE
+THE REQUIREMENTS FOR | THE REQUIREMENTS FOR| REQUIREMENTS FOR
+THE DEGREE OF (Name | THE DEGREE OF (Name of THE
+of Programme) Programme) DEGREE OF
+(Name of
+Programme)
+
+### Page 147
+This page is the first page of Roman numeral page number but it is not numbered. The
+text should be typed using font type Times New Roman, font size 14 with 1.15 pt. line
+spacing.
+(a) (b)
+ITTLE OF DISSERTATION
+TITLE OF RESEARCH REPORT
+NAME OF CANDIDATE
+NAME OF CANDIDATE
+DISSERTATION SUBMITTED IN
+SUBMITTED TO THE GRADUATE PARTIAL FULFILMENT OF THE
+“HOOL OF BUSINESS AND REQUIREMENTS FOR THE DEGREE
+ACCOUNTANCY UNIVERSITI (OF MASTE
+MALAYA, IN PARTIAL FULFLMENT
+REQUIREMENTS FOR THE
+GREE OF MASTER OF BUSINESS son paeuy aye) acs
+ADMINISTRATION NAME OF FACULTY / ACADEMY
+INSTITUTE /CENTRE
+UNIVERSITI MALAYA
+20x KUALA LUMPUR
+200x
+() @)
+TITLE OF DISSERTATION
+NAME OF CANDIDATE
+DISSERTATION SUBMITTED IN
+FULFILMENT OF THE
+REQUIREMENTS FOR THE
+NAME OF FACULTY / ACADEMY /
+INSTITUTE / CENTRE
+UNIVERSITI MALAYA
+KUALA LUMPUR
+202x
+TITLE OF DISSERTATION
+NAME OF CANDIDATE
+DISSERTATION SUBMITTED IN
+PARTIAL FULFILMENT OF THE
+REQUIREMENTS FOR THE DEGREE
+OF DOCTOR OF MANAGEMENT
+NAME OF FACULTY / ACADEMY
+INSTITUTE / CENTRE
+UNIVERSITI MALAYA
+KUALA LUMPUR
+202x
+
+### Page 148
+Figure 2.1, continued
+(e)
+TITLE OF THESIS
+NAME OF CANDIDATE
+THESIS SUBMITTED IN PARTIAL
+FULFILMENT OF THE
+REQUIREMENTS FOR THE DEGREE.
+‘OF DOCTOR OF PUBLIC HEALTH
+NAME OF FACULTY / ACADEMY
+INSTITUTE / CENTRE
+UNIVERSITI MALAYA
+KUALA LUMPUR,
+202x
+NAME OF CANDIDATE
+THESIS SUBMITTED IN
+FULFILMENT OF THE
+REQUIREMENTS FOR THE DEGREE
+‘OF DOCTOR OF PHILOSOPHY /
+MEDICINE
+NAME OF FACULTY / ACADEMY /
+INSTITUTE / CENTRE
+UNIVERSITI MALAYA
+KUALA LUMPUR
+202%
+Figure 2.1: Examples of title page
+(a) Master's research report by coursework and by clinical, (b) Master's dissertation by Mixed
+mode, (c) Master's dissertation by research, (d) Doctoral dissertation by coursework and by
+clinical, () Doctoral thesis by mixed mode, and (f) Doctoral thesis by research.
+
+### Page 149
+TITLE OF THESIS.
+NAME OF CANDIDATE
+THESIS SUBMITTED IN PARTIAL
+FULFILMENT OF THE
+REQUIREMENTS FOR THE DEGREE.
+OF DOCTOR OF PUBLIC HEALTH
+NAME OF FACULTY / ACADEMY
+INSTITUTE / CENTRE
+UNIVERSITI MALAYA
+KUALA LUMPUR,
+TITLE OF THESIS
+NAME OF CANDIDATE
+THESIS SUBMITTED IN
+‘OF DOCTOR OF PHILOSOPHY /
+MEDICINE
+NAME OF FACULTY / ACADEMY.
+INSTITUTE / CENTRE
+UNIVERSITI MALAYA
+KUALA LUMPUR
+7 202x,
+Figure 2.1: Examples of title page
+(a) Master's research report by coursework and by clinical, (b) Master's dissertation by Mixed
+mode, (c) Master's dissertation by research, (d) Doctoral dissertation by coursework and by
+clinical, (e) Doctoral thesis by mixed mode, and (f) Doctoral thesis by research
+2.1.2 Original Literary Work Declaration
+This form must be completed by the candidate and signed by a witness (Supervisors
+or Head of Department/Deputy Dean of Postgraduate). The original signed form must
+be included in all copies of the research report/dissertation/thesis. The form can be
+downloaded from the MAYA website in two (2) languages (English and Bahasa
+Malaysia). If the research report/dissertation/thesis is written in English, hence the
+English version of the form is used and vice versa.
+
+### Page 150
+@ ven MALAA (b)
+Figure 2.2: Original Literary Work Declaration
+(a) English, (b) Bahasa Malaysia
+
+### Page 151
+2.1.3 Abstract
+An abstract is a short summary of the research report/dissertation/thesis. An abstract
+should briefly describe the objectives of the research (problem statement), the
+significance of the research, research methodology, as well as the findings and
+conclusion of the research.
+The Abstract page begins with the title of research report/dissertation/thesis (in
+uppercase) that is approved by the faculty. Candidates are not allowed to change the
+title without the approval of the faculty.
+‘An abstract must not exceed 500 words, typed in a single paragraph with double-
+spacing, and written in Bahasa Malaysia and English language. A maximum of five (5)
+keywords should also be listed below the abstract (Figure 2.3).
+Where the language of the thesis is other than Bahasa Malaysia [Malaysia] or English
+[United Kingdom], an abstract in that language must also be included. The sequence
+of abstracts is as follows:
+= For research report /dissertation/thesis written in Bahasa Malaysia, the abstract in
+Bahasa Malaysia is followed by the English version.
+* For research report /dissertation/thesis written in English, the abstract in English is
+followed by the Bahasa Malaysia version.
+= For research report /dissertation/thesis written in Arabic, the abstract in Arabic is
+followed by its version in Bahasa Malaysia and English.
+The Abstract page is assigned Roman numeral "ii" and the following pages should be
+numbered consecutively.
+
+### Page 152
+[TITLE OF RESEARCH REPORT/DISSERTATION/THESIS]
+ABSTRACT
+The purpose of this aesthetic evaluation is two-fold. First, I examine J.R.R. Tolkien’s literary illustration of
+space, place, and atmosphere in a series of locations across Middle-earth, I focus on the aesthetic facets of
+the physical environments, the possible aesthetic experiences generated from the visual layers of landscapes
+and atmospheres, and finally, the philosophical implications obtained through the moments of reflection in
+those locations. Second, I investigate the possibility of considering Tolkien’s depiction of space, place, and
+atmosphere as literary artifacts and the construction of the whole Middle-earth as an act of antistic creation.
+The theoretical framework of this doctoral research is formulated based on the combination of seven critical
+criteria consisting of formalism, framing, historical/biographical information, imagination, the dialectical,
+engagement, and aesthetic creation theory taken from environmental aesthetics and art philosophy. ‘These
+critical terms are tools at hand in aesthetically determined forms of evaluation and appret
+ion, Which allows:
+assessing the qualitative—lterary—landscapes fom multiisciplinary views to interpret their aesthetic and
+philosophical significance. Results demonstrate that Middle-earth could be observed as an aesthetico-cultural
+tapestry on which Tolkien materialized his artistic, creative, moral, social, and environmental concerns
+regarding the grave era in which he lived. He accomplished this task through the depiction of perceptual
+aesthetic dimensions of the literary environments. Therefore, Middle-earth could stand as more than a mere
+background of The Lord of the Rings; thus, the shaping of this imagined realm can be identified as an act of
+art creation. Further, the aesthetic decoration and juxtaposition of the physical environments and artifactual
+objects in Middle-earth make them eligible to be viewed as literary artifacts. The findings of this research
+can crucially contribute to our understanding of JR.R. Tolkien as a literary world-builder who externally
+depicted the landscapes of Middle-earth with aesthetic features and intemally elevated them with
+philosophical dimensions to convey his moral, philosophical, artist
+and environmental messages. The
+results could also assist scholars in arts and humanities in illuminating how the representation of imagined
+geography could be utilized as a powerful aesthetic tool to demonstrate thought-provoking aesthet
+philosophical spaces of contemplation
+Keywords: JRR. Tolkien, Middle-earth, literary Landscapes, Aesthetic Creation, Environmental
+Acsthet
+ii)
+Figure 2.3: Example of abstract
+
+### Page 153
+2.1.4
+2.1.5
+2.41.7
+2.18
+Acknowledgements
+Most research reports, dissertations or theses include a message to convey
+appreciation to those who have been involved and provided their assistance directly or
+indirectly in the preparation of the study.
+This is optional and should not exceed a single page, which is numbered in Roman
+numeral accordingly.
+Table of Contents
+The Table of Contents lists the chapters, topics and sub-topics together with their page
+numbers. Sub-topics and topics should be labelled according to the chapter, for
+example:
+CHAPTER 1: TITLE
+1.1 Topic 1
+1.1.1 Sub-topic 1
+CHAPTER 2: TITLE.
+2.1 Topic 1
+2.1.4 Sub-topic 1
+This numbering system provides a clear picture of the relationship between chapters
+and topics and shows how they are connected.
+List of Figures
+This list contains the titles of figures, together with their page numbers, which are found
+throughout the text. For example, figures in Chapter 1 are numbered sequentially:
+Figure 1.1, Figure 1.2 and so on.
+List of Tables
+This list contains the titles of tables, together with their page numbers, which are listed
+in the text. The numbering system is according to chapter, for e.g.: tables in Chapter 1
+are numbered sequentially: Table 1.1, Table 1.2 and so on.
+List of Symbols and Abbreviations
+The symbols, abbreviations, nomenclature and terminology that are used in the text
+must be listed down accordingly.
+For further information on spelling and abbreviations, candidates are advised to refer to
+the latest edition of the Oxford Advanced Learner's Dictionary published by Oxford
+University Press.
+
+### Page 154
+2.1.9 List of Appendices
+This list is optional and contains the titles of appendices placed in the supplementary
+section
+2.2 Main Body
+Candidates and supervisors should ensure that the text follows the agreed conventions of the
+individual faculty. The main body in the research report/dissertation/thesis must be organized
+following the guidelines as mentioned below:
+* Text must be organized in titled chapters.
+The chapter titles must reflect the content of the chapter.
+« Every chapter must begin on a new page.
+* Chapters can be divided into sub-chapters with corresponding sub-titles.
+* Titles and sub-titles must be numbered.
+There is no restriction on the total number of chapters in a research report/dissertation/thesis.
+The number of chapters differs according to the field of study conducted by the candidate
+whether it is science-based or social science-based. However the content of the chapters may
+differ according to the candidate's research or conventions of individual faculty.
+Generally, a research report/dissertation/thesis will have the following basic structure:
+* INTRODUCTION
+* LITERATURE REVIEW
+* METHODOLOGY
+* RESULTS
+* DISCUSSION
+* CONCLUSION
+* REFERENCES
+Items in the structure are divided into separate chapters and the descriptions of these chapters
+are as follows:
+22.1 Introduction
+This chapter contains the introduction to the issues in which the research is concerned
+with, the aims and objectives of the study, and the scope or outline of the research
+approach as well as the structure of the research report/dissertation/thesis.
+222 Literature Review
+Alliterature review is a description of the literature relevant to a particular field or topic
+of study. It consists of a critically written and comprehensive account of the published
+works on a topic by accredited scholars and researchers. A critical literature review is a
+critical assessment of the relevant literature. It is directly related to the research,
+providing information on theories, models, materials and techniques used in the
+research. The literature review should be comprehensive and include recent
+publications which are relevant to the research.
+
+### Page 155
+Methodology
+This chapter describes and explains the materials as well as the research methodology
+used in the study. The sub-topics for this chapter include the key research questions,
+the research design, and the research procedures adopted. It may also, where
+appropriate, indicate sampling methods, research instruments and statistical methods
+employed. The purpose of this is to inform the reader on the methods used to collect
+the data and generate the findings reported.
+Results
+This chapter explains the results which are commonly presented in the form of text,
+figures and tables, complete with data analysis.
+Discussion
+This chapter contains the interpretation of the results. The findings of the research
+should be compared and contrasted with those of previous studies presented in the
+literature review. The purpose of this chapter is to discuss the findings and the outcomes
+of the research in relation to the results that have been obtained.
+Conclusion
+In this chapter, the findings are summarized and their implications discussed. This
+section may include suggestions for future work.
+References
+All works or studies referred to in the research report/dissertation/thesis in the form of
+quotations or citations must be included in the references.
+The references should be written consistently according to the official citation guide
+approved by the faculty.
+APA Format
+Each reference should be written in single spacing format and a double space should
+be left between references. The list of references must be arranged in alphabetical
+order and theentries should not be numbered. The list must also have a hanging
+indentation of 0.5 inch. For example:
+Walmsley, Ben. (2019), Audience Engagement in the Performing Arts: A Critical
+Analysis. Springer Nature.
+Wreen, Michael. (2014) “Beardsley’s Aesthetics.” The Stanford Encyclopedia of
+Philosophy, edited by Edward N. Zalta, Winter 2014, Metaphysics Research Lab,
+Stanford University.
+Tillson, Victoria G. (2010) "A Nearly Invisible City: Rome in Alberto Moravia's
+1950s fiction." Annali d'Italianistica, 28: 237-256.
+
+### Page 156
+Reference citations in text require the following information:
++ last name of the author or as specified in the UM Library APA Formatting and Style
+Guide (latest edition),
++ the year of publication,
++ the page number for the reference (direct quotes only).
+For summaries or paraphrases, the last name of the author and the year of publication
+must be included for the in-text reference. For examples:
+Kingston and Parker (2012) found the biggest challenges in classroom to be .
+The biggest challenges in classroom were .... (Kingston & Parker, 2012).
+For direct quotations (which refers to when the exact words of another author are
+copied), the last name of the author, the year of publication as well as the page number
+for the reference must be included for the in-text reference. The quotation has to be
+enclosed in quotation marks. For examples:
+In Unfinished Tales of Numenor and Middle-earth (1980), Christopher writes
+that his father illustrated mallom trees based on familiar Primary World species.
+Gollum enter the damned land of Sauron. Tolkien describes the scenery from
+the eyes of the hobbits and writes, “slowly and painfully they clambered down,
+groping, stumbling, scrambling among rock and briar and dead wood in the
+blind shadows” (The Lord of the Rings, 917),
+
+### Page 157
+If the quoted citation contains more than 40 words, it should be placed within a
+paragraph of its own with a 0.5 inch indentation. For example:
+Thacker could answer that question too when he contends that “since the early
+1990s questions of space and geography have become recognized as legitimate
+and important topics in many areas of literary and cultural studies, and setting out
+the sphere of literature, if not life, by some form of map a more familiar
+hermeneutic strategy” (The Idea of a Critical Literary Geography, 57-8). Itis,
+therefore, fruitful to carry out an analysis of Tolkien’s watercoloresque
+melancholic visualization of space, place, and atmosphere and observe them as
+Tolkien's critique of the destructive nature of modernity that parallels with
+contemporary environmental concerns.
+Please refer to the Universiti Malaya Library APA Formatting and Style Guide. The
+guide can be downloaded at UM Library website (https://umlibguides.um.edu.my)
+Other Citation Format
+For reference citation in-text and list of references using other than the APA format,
+please refer to the official citation guide associated. For example, in American
+Chemistry Society (ACS) style, the citation format for in-text citation is as follows:
+The mineralization of TCE by a pure culture of a methane-oxidizing organism has been reported (6)
+Meanwhile the list of reference that contains full bibliographic information at the end of
+the research report/dissertation/thesis should appear as one numerical sequence in the
+order that the material is cited is as follows:
+References
+4. Hoppert, M. Microscopic Techniques in Biotechnology; Wiley-VCH: Weinheim, 2003; pp 145-158.
+5. Klinger, J. Influence of Pretreatment on Sodium Powder. Chem. Mater. 2005, 17, 2755-2768
+6. Ford H. L.; Sclafani R. A; Degregori J. Cell Cycle Regulatory Cascades. In Cell Cycle and Growth
+Control: Biomolecular Regulation and Cancer, 2nd ed.; Stein G. S., Pardee A. B., Eds.; Wiley-
+Liss: Hoboken, NJ, 2004; pp 42-67.
+
+### Page 158
+2.3. Supplementary
+Specific items which were not included in the main body of the text, should be put in this
+Supplementary section. Typically, this section includes the following:
+234. List of Publications and Papers Presented
+Published works as well as papers presented at conferences, seminars, symposiums
+etc. pertaining to the research topic of the research report/dissertation/thesis are
+suggested be included in this section. The first page of the article may also be
+appended as reference.
+232 Appendices
+Appendices consist of research instruments, additional illustration of data sources, raw
+data and quoted citations which are too long to be placed in the text. The appendix
+section supports the written text of the research report/dissertation/thesis by including
+materials that can provide additional information. These materials include research
+data, tables, examples of questionnaires, maps, photos and other materials that are
+too long to be included in the text or are not directly required to comprehend the text
+can be included as appendices.
+Tables and graphics that are more than two pages long are suggested to be included
+in the Appendix section
+Appendices are labelled as APPENDIX A, APPENDIX B, etc. and they should
+correspond to the List of Appendices of Preliminary section.
+233 Co-authors Consent
+Please refer to 1.3 (d).
+CHAPTER 3: FORMAT SPECIFICATIONS
+3.1 Paper Quality, Printing and Duplicating
+The research report/dissertation/thesis should be printed, single-sided, on high quality white
+‘A4 paper (201 x 297 mm; 80 grams). Computer pin-feed printout paper is not permitted.
+The research report/dissertation/thesis, in soft cover copies, must be typed and duplicated by
+offset printing or good quality photocopying. All copies must be clean and neat in order to
+ensure easy reading.
+3.2 Typing and Printing Quality
+Texts in research report/dissertation/thesis should be typed on one side of the paper only.
+They must be typed using font type Times New Roman, font size 12 (except for tables and
+figures) and justified, using Microsoft Word version (latest edition) or later, or similar word-
+processing software. Those written in Arabic should use font type Traditional Arabic in font
+size 16. Words in a language that is different from the language of the research report
+/dissertation/thesis must be typed in italics. For mathematical texts, the use of Equation Editor
+or LaTeX is advisable. Script fonts are not permitted.
+
+### Page 159
+Chapter titles should be typed with capital letters and centered between the left and right
+margins. Each chapter must begin on a new page. Chapters and subchapters should be also
+titled, Titles should be typed in bold without underline.
+A high-quality laser or ink-jet printer should be used for the printing.
+3.3. Line Spacing
+The body of the text should be typed with double spacing. Single-spacing is only permitted in
+tables, long quotations, footnotes, citation and in the references.
+The first sentence of a new paragraph should not start at the bottom of a page if the space
+available can only fit one line.
+3.4 Margins
+The text should have the following margins:
+* Top 0 cm or 0.79 inch
+« Right .0 cm or 0.79 inch
+° Left : 4.0 cm or 1.57 inch
+* Bottom : 2.0 cm or 0.79 inch
+Additional guidelines regarding margin are as follows:
++ Do not type more than one sentence after the bottom margin. If it is necessary to do so, it
+‘should only be for a footnote or the completion of the last sentence of the chapter, topic or
+sub-topic or information in a figure.
+
+### Page 160
+3.5
+All tables and figures must be placed within the specified margins.
+The last paragraph of the page should contain at least two sentences. If it does not, the
+paragraph should begin on the next page.
+Page Numbering
+All page numbers should be printed 1.0 cm from the bottom edge of the page and placed at
+the
+right-hand side without any punctuation (Figure 3.1).
+The page numbering system must conform to the following rules:
+3.6
+The page numbers should be placed at the right-hand side without any punctuation.
+Font type Times New Roman and font size 10 recommended for numbers
+Roman numerals (i, ii, ili, ...) should be used in the Preliminary section, The first page of
+the thesis, the title page, is an unnumbered page ‘i’. Numbering begins on the second page
+with ‘ii’ for the Original Literary Work Declaration Form.
+Arabic numerals (1, 2, 3, ...) are used on the pages of the text (starting with the Introduction
+page) and Supplementary section.
+Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor;
+incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud
+dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
+exercitation ullameo laboris nisi ut aliquip ex ea commodo consequat, Duis aute inure} [Ip fine with text
+Excepteur sint occaecat cupidatat non proidpnt, sunt in culpa qui officia deserunt mollit
+anim id est laborum
+4] Approximately 1 em
+Figure 3.1: Placement of page number
+Numbering of Chapters and Sub-chapters
+Chapters and sub-chapters must be numbered using Arabic numerals (1, 2, 3 etc).
+Chapters are numbered CHAPTER 1, CHAPTER 2, CHAPTER 3, and so on. Sub-
+chapters are nested, but its numbering is not indented, up to a maximum of 4 levels as
+in the example shown below:
+CHAPTER 2: FIRST LEVEL (CHAPTER TITLE)
+2.1 Level 2 (sub-title);
+2.1.1 Level 3 (sub-sub-title);
+2.1.1.1 Level 4 (sub-sub-sub-title)
+
+### Page 161
+3.7
+The use of letters in parenthesis in the main body for e.g., (a), (b), (c) is appropriate as
+a means of differentiating sub-topics of the same topic. However, it is not required to
+be listed in the Table of Contents.
+If a chapter title or chapter sub-title at any level exceeds a single line, the spacing
+between the lines must be the same as that of the text (double-spacing). Subsequent
+sub-chapters beyond the fourth nesting level must be numbered using alphabets; (a),
+(b), (c), and so on.
+Footnotes
+There are differences in the use of footnotes in various disciplines. For example,
+footnotes are commonly used in Social Sciences research but rarely in Sciences
+research. However, candidates are advised to limit the use of footnotes unless they are
+proved necessary to the document. Footnotes are used to elaborate or provide
+additional information regarding matters discussed in that page.
+Footnotes are recorded using Arabic numeric and numbered consecutively. Raised
+superscript numerals in the text refer to explanatory notes and documented sources
+appearing either at the bottom of the page as footnotes or at the end of the thesis as
+endnotes in a notes section. The advantage of using notes is that explanatory type of
+information can be presented along with source citations on the same page or place.
+Footnotes should use a smaller font than the text (font size 8).
+When using footnote, a number formatted in superscript is inserted following the
+punctuation mark in the text. Footnotes should be placed at the bottom of the page on
+which they appear (Figure 3.2). Please refer to the faculty for the recommended
+convention for writing of footnotes.
+Western ideas of art, civilization, and philosophy was first discussed by Plato]
+in The Republic (381 BC).
+» Gardner,
+Press, 1999
+ebastian. Routledge Philosophy Guidebook to Kant and the Critique of Pure Reason. Psychology
+Figure 3.2: Example of footnote
+
+### Page 162
+3.8 Tables
+Tables are printed within the body of the text at the center of the frame and labelled according
+to the chapter in which they appear. Thus, for example, tables in Chapter 3 are numbered
+sequentially: Table 3.1, Table 3.2 and so on.
+The caption should be placed above the table itself (Table 3.1). If the table contains acitation,
+the source of the reference should be included in the table caption.
+Table 3.1: Example of table
+Heading Heading
+Text Text
+If the table occupies more than one page, the continued table on the following page should
+indicate that it is a continuation, for example: ‘Table 3.7, continued’. The header row should
+also be repeated.
+3.9 Figures
+Figures, like tables are printed within the body of the text at the center of the frame and labelled
+according to the chapter in which they appear. Thus, for example, figures in Chapter 3 are
+numbered sequentially: Figure 3.1, Figure 3.2.
+Figures, unlike text or tables, contain graphs, illustrations or photographs and their labels are
+placed at the bottom of the figure rather than at the top (using the same format used for tables)
+(Figure 3.3).
+: |
+Fexample
+20 "
+‘Sample
+Figure 3.3: Example of figure
+If the figure occupies more than one page, the continued figure on the following page should
+indicate that it is a continuation: for example: ‘Figure 3.7, continued’.
+If the figure contains a citation, the source of the reference should be placed after the label.
+mm
+
+### Page 163
+3.10 Binding
+Each copy of the research reportidissertation/thesis submitted shall be bound in one (1)
+volume. The thesis cover must be of A4 size (210mm x 297mm).
+For the purpose of examination, research report/dissertation/thesis submitted should be soft
+cover or comb bound with the following colour (Figure 3.4)
+‘+ Research report: Navy blue
+‘* Dissertation: Dark red or maroon
+‘© Thesis: Dark red or maroon
+For final submission prior to graduation, research report/dissertation/thesis submitted should
+be compulsorily in soft copy or optionally in hard copy. If the faculty requires hard copy, the
+document should be hard cover bound in rexine with the following colour (Figure 3.5):
+‘* Research project: Navy blue
+‘* Dissertation: Dark red or maroon
+‘* Thesis: Dark red or maroon
+Front Cover Colour of Dissertation/Thesis (Dark red or maroon)
+Front Cover Colour of Research Report (Navy blue)
+Figure 3.4: Sample of softbound / comb bound copy for first submission for examination
+
+### Page 164
+(a)
+Figure 3.5: Samples of hardbound copy for final submission
+@ Example of hardbound thesis or dissertation (in dark red or maroon);
+(b) Example of hardbound research report (in navy blue)
+
+### Page 165
+The title of research report/dissertationAhesis, name of author, name of the University
+and year of submission must be printed on the front cover. The letters for the Front
+Cover should be printed in gold letterings of font size 16, font type Arial Narrow,
+bold and in uppercase letters (Figure 3.6 and 3.7).
+TITLE OF RESEARCH PROJECT |
+——_— DISSERTATION | THESIS <I
+NAME OF CANDIDATE
+FACULTY OF ...
+UNIVERSITI MALAYA
+KUALA LUMPUR
+202K
+Figure 3.6: Formatting of the front cover of research report/dissertation/thesis
+mm
+
+### Page 166
+‘TITLE OF RESEARCH
+THATIS APPROVED.
+BY THE FACULTY
+GOLD LETTERING, . NAME OF
+FONTARIAL ee a CANDIDATE AS
+NARROW, SIZE 16 REGISTERED WITH
+BOLD, 1.15 PT. LINE THE UNIVERSITY
+SPACING
+FACULTYIACADEMY!
+INSTITUTE/CENTRE
+WHERE CANDIDATE
+IS REGISTERED
+YEAR OF
+‘SUBMISSION.
+Figure 3.7: Example of the front cover of research report!
+dissertationithesis
+
+### Page 167
+The spine of the manuscripts should show the title of research report/dissertation/thesis, name
+of author, year of submission and name of degree. The year of submission must be in
+accordance with the year when the research report/dissertation/thesis is submitted (Figure3.8
+and 3.9), If the title of the research report/dissertation/thesis exceeds the space of the spine,
+a smaller font size can be used (i.e. font size 16 to 14) or alternatively the title can be truncated
+with ellipses (...) (Figure 3.10)
+PRIVATIZATION IN ALGERIA: POLICY AND PhD
+‘AMIR GHORRANL PERFORMANCE 2017
+Figure 3.8: Spine format
+AYANPAUL
+Figure 3.9: Example of spine format
+THE EFFECT OF GEOGRAPHICAL REGION ON rn)
+KWONG SIU YEE THE TRANSITION TIME OF CMMI-BASED ... 2017
+Figure 3.10: Spine format for long title
+3.11. Word Limit
+The maximum word limit for a submission for examination is shown in Table 3.2.
+Table 3.2: Maximum word limit
+Master's Programme
+Research Report Dissertation (by Dissertation
+(by Coursework Mixed mode) (by
+or by Clinical) Research)
+30,000 words 40,000 words 60,000 words
+Doctoral Programme
+Dissertation (by Thesis Thesis (by
+Coursework or (by Mixed Research)
+by Clinical) mode)
+60,000 words 80,000 words 100,000 words
+
+### Page 168
+The minimum word limit is determined by the faculty or based on the programme standards
+according to their respective discipline (if any). The maximum length of words excludes
+footnotes, references, appendices, tables, figures and prefaces.
+Candidates who are unable to meet the word limit set by the University must seek approval
+from the faculty at least one month before the submission of research report
+Idissertation/thesis for examination.
+3.12 Other Information
+A candidate may not resubmit previous research work which he has submitted to this or any
+other university for the award of a degree. The candidate may, however, incorporate any part
+of such work, provided that there is a clear indication in the research report/dissertationithesis
+of its sources.
+The candidate may also include any other printed or published work by an individual or a
+working group to validate his findings. Where the contribution is from a working group, the
+candidate is required to provide a statement indicating which part of the work was carried out
+by the candidate. The statement should be signed by the rest of the group indicating their
+consent (this may be included in the Appendix).
+Approved research report/dissertationsitheses or parts of their content are allowed for
+publication if they are accompanied by a statement that the work was conducted towards the
+fulfilment of a particular degree.
+Candidates of Doctoral degree (all modes) and Master's by research are required to publish
+papers in Web of Science (WoS) or Scopus or "Category A or B refereed journals or book or
+Spook chapters publish by publishers listed in the WoS, Universiti Malaya Press, or Dewan
+Bahasa dan Pustaka or any publishers recognized by the Faculty. Publications must be based
+on the work during the course of study, and due reference must be made to the University
+associated guidelines and requirements in all such papers.
+
+### Page 169
+CHAPTER 4: SUBMISSION
+44 Prior to Submission
+Postgraduate candidates are required to obtain approval from the supervisor(s) and faculty via
+MAYA before online submission. This is to allow timely nomination of examiners for research
+report/dissertation/thesis.
+Submission of research report/dissertationithesis for examination has to be done within the
+candidature period after title approval by the faculty.
+Candidates are strongly advised against copying the formatting done by other candidates as
+previously submitted research reportidissertation/thesis may not conform to the current
+formatting requirements. Failure to meet the formatting requirements may resutt in a research
+repottithesis/dissertation being rejected at the point of submission.
+Postgraduate candidates shall submit at least one (1) electronic PDF copy of their research
+report/dissertations/theses to the Postgraduate Officer of the respective faculty.
+4.2 Required Documents for Submission
+42.1 Documents required for submission for the purpose of examination are as
+follows:
+* at least two (2) printed softbound/comb bound copies (or such numbers as
+may be determined by the faculty) of the research reportidissertation/thesis;
+© one (1) electronic copy (PDF format) which is not under limited/blocked
+mode; and
+‘+ Submission of Thesis / Dissertation for Examination/Re-examination form.
+42.2 Documents required for final submission prior to graduation after
+completing the corrections (if any), are as follows:
+‘* at least one (1) printed hardbound copy (or such numbers as may be
+determined by the faculty) of the final research reportidissertation/thesis,
+(subject to the faculty requirement);
+‘* one (1) electronic copy (PDF format) which is not under limited/blocked
+mode;
+* Final Submission of Thesis/Dissertation form;
+‘* ‘The Candidate's Declaration form;
+* Repository Policy for_—_Universit, Malaya Postgraduate
+Theses/Dissertation/Research Reports form; and
+‘* Correction Report form (if applicable).
+All the required forms can be downloaded from the MAYA portal in the
+https://umsitsguide.um.edu.my/index. htm
+“ This form shall be labelled according to the year of submission of the thesis/dissertation/research report followed by
+student ID and the word ‘perakvan’. For example: 2023_170261111_perakuan.
+
+### Page 170
+The submitted electronic copy of the research report/dissertation/thesis (in PDF format)
+in a USB flash drive or any valid source of electronic copy must be labeled with the
+following details:
+© Name
+* Registration no.
+* Title of research report/dissertation/thesis
+* Faculty/Academy/Institute/Centre
+© Year of submission (current year)
+Once all the documents required for final submission is completed, the faculty shall
+submit the documents via email to thesis@365.um.edu.my.
+
+### Page 171
+CHAPTER 5: PLAGIARISM
+Postgraduate candidate of the Universiti Malaya are expected to produce original academic
+work. Plagiarism is defined as an academic fraud arising from the attitude of lying, insincerity,
+untrustworthiness, dishonesty and disrespect to fellow colleagues. Plagiarism happens when
+someone else's idea is taken without mentioning the source, and thus giving the impression
+that the idea is his own. This situation may occur when:
+(1) one's idea, taken word for word from an article or book that has been published.
+(2) The idea of a person from an article or book is taken using his own words.
+(3) A person's idea is taken from discussions whether in conferences, seminars, forums, talks
+or informal discussions between two parties.
+(4) Data, diagrams, tables, photographs or any other illustrative material derived from others is
+taken as if it were his own.
+Postgraduate candidates are strongly advised to read the Universiti Malaya Guidelines on
+Handling Plagiarism, which outlines the rules and regulations pertaining to acts of plagiarism.
+The University also requires the usage of Turnitin, an online web-based plagiarism detection
+application to avoid plagiarism and academic dishonesty. In most cases, the similarity index
+percentage should be between 10% to 30% and/or Artificial Intelligence (Al) writing detection
+indicator of more than 10%. Please refer to your respective faculty regarding the acceptable
+similarity index percentage.
+
+
+## Research Guidance :: Thesis or Dissertation Submission and Examinations
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 172-172
+
+
+
+## Research Guidance :: Publication Requirement
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 173-175
+
+### Page 173
+PUBLICATION
+REQUIREMENT
+PUBLICATION REQUIREMENT FOR POSTGRADUATE CANDIDATES BY RESEARCH
+(SENATE APPROVAL ON 28.5.2015)
+DOCTORAL CANDIDATES
+(1) Doctoral candidates pursuing programmes in the field of Sciences must show
+proof of acceptance for publication of at least two (2) articles in journals
+indexed by Thomson Reuters Web of Science (WoS) (according to the
+criteria set in the publication guidelines), prior to graduation.
+(2
+Doctoral candidates pursuing programmes in the field of Social Sciences
+must show proof of acceptance for publication as per the following (according
+to the criteria set in the publication guidelines), prior to graduation:
+()) at least one (1) article in journals indexed by Thomson Reuters Web of
+Science (WoS)
+or,
+(ii) at least one (1) book published by publishers listed in the Thomson
+Reuters Web of Science (WoS) Master Book List or by University of
+Malaya Press or Dewan Bahasa dan Pustaka or any publishers
+recognized by the Faculty
+or,
+(ii) at least two (2) publications in Category A or B refereed journals, or book
+chapters as follows:
+* Articles in Category A journals:
+Journals indexed in the Scopus citation database; or the ERA
+Journal List (Australian Research Council).
+* Articles in Category B journals:
+Journals published by University or scholarly publishers or listed in
+MyJurnal (Malaysian Journal Management System). (List of
+Category B journals must be recognized by the Faculty),
+* Book chapters in different books:
+Book chapters published by publishers listed in the Thomson
+Reuters Web of Science (WoS) Master Book List, or by University of
+Malaya Press or Dewan Bahasa dan Pustaka or any publishers
+recognized by the Faculty. Two (2) book chapters in different books
+are equivalent to one (1) publication
+
+### Page 174
+PUBLICATION
+REQUIREMENT
+PUBLICATION REQUIREMENT FOR POSTGRADUATE CANDIDATES BY RESEARCH
+(SENATE APPROVAL ON 28.5.2015)
+MASTERS CANDIDATES
+(1)
+(2)
+Master's candidates pursuing programmes in the field of Sciences must show
+proof of acceptance for publication of at least one (1) article in journals
+indexed by Thomson Reuters Web of Science (WoS) (according to the
+criteria set in the publication guidelines), prior to graduation.
+Master's candidates pursuing programmes in the field of Social Sciences
+must show proof of acceptance for publication as per the following (according
+to the criteria set in the publication guidelines), prior to graduation:
+(i) at least one (1) article in journals indexed by Thomson Reuters Web of
+‘Science (WoS)
+or;
+(ii) at least one (1) book published by publishers listed in the Thomson
+Reuters Web of Science (WoS) Master Book List or by University of
+Malaya Press or Dewan Bahasa dan Pustaka or any publishers
+recognized by the Faculty
+or;
+(iii) at least one (1) publication in Category A or B refereed journals, or book
+chapters as follows
+* Articles in Category A journals:
+Journals indexed in the Scopus citation database; or the ERA
+Journal List (Australian Research Council).
+* Articles in Category B journals:
+Journals published by University or scholarly publishers or listed in
+MyJumal (Malaysian Journal Management System). (List of
+Category B journals must be recognized by the Faculty)
+* Book chapters in different books:
+Book chapters published by publishers listed in the Thomson
+Reuters Web of Science (WoS) Master Book List, or by University of
+Malaya Press or Dewan Bahasa dan Pustaka or any publishers
+recognized by the Faculty. Two (2) book chapters in different books
+are equivalent to one (1) publication.
+
+### Page 175
+PUBLICATION GUIDELINES FOR POSTGRADUATE CANDIDATES BY RESEARCH
+(SENATE APPROVAL ON 28.5.2015)
+Publication(s) produced by postgraduate candidates (research mode) in fulfilment of graduation
+requirements must comply with the following criteria:
+CRITERIA
+REMARK
+(1) Type of Publications
+Publications accepted must be:
+‘© fulllength articles in journals with impact factor, which are listed in:
+(a) Thomson Reuters Web of Science (WoS) databases (Science
+Citation Index Expanded™, Social Sciences Citation Index® and
+Arts & Humanities Citation Index®) or;
+(b) Category A* or Category B* recognized by the faculty; or;
+* books" or book chapters* published by publishers listed in the ISI Web
+of Science (WoS) Master Book List, Thomson Reuters or by University
+of Malaya Press or Dewan Bahasa dan Pustaka or any publishers
+recognized by the Faculty. One (1) book is equivalent to 2 (two)
+Publications whereas two (2) book chapters in different books are
+equivalent to 1 (one) publication.
+“Note: Publications in Category A or Category B refereed journals or
+books or book chapters are only applicable to candidates pursuing
+programmes in the field of Social Sciences.
+(2) Authorship
+Publications accepted must be published with the supervisor(s).
+The candidate must be the first author, or either the second or subsequent
+author after the supervisor(s), or the first student author. In the event
+where two or more candidates co-authored an article, only one candidate
+is allowed to use this article to fulfil his/her graduation requirement.
+(8) Timing
+Publications accepted must be within the candidature of the candidate
+(4) Topic of publications
+Publications accepted must be related and conform to the candidate's
+research in his/her thesis/dissertation.
+(8) Affiliation
+Publications accepted must carry the affiliation of the department and/or
+faculty where the candidate is registered.
+(6) Blacklisted journals
+Publications in the following journals are NOT accepted
+Publications in journals blacklisted by the Malaysian Ministry of
+Education (MoE)
+* Publications in Probable Predatory Journals
+(http://scholarlyoa.com/individual-journals/) and Publishers
+(http:/scholarlyoa.com/publishers/) and hijacked journals
+(http://scholarlyoa.com/other-pages/hijacked-journals/) according to
+Beall's List.
+
+
+## Research Guidance :: Plagiarism
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 176-176
+
+### Page 176
+PLAGIARISM
+AVOIDING PLAGIARISM
+As an enrolled student and member of the Universiti Malaya candidates are expected
+to produce original academic work. Failure to acknowledge the work of others in their
+work means the candidate is guilty of plagiarism. A candidate who is found to have
+plagiarized his assignments or any written work that is part of the assessment in a
+course or programme may be subjected to disciplinary action under the Universiti
+Malaya .
+Candidates are advised to check their work for originality by using the Turnitin
+software. Details on Turnitin software can be accessed at https:/Avww.turnitin.com
+
+
+## Research Guidance :: Intellectual Property
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 177-177
+
+### Page 177
+INTELECTUAL PROPERTY
+The UM —Intellectual Property Policyll covers intellectual property (IP) ownership. As
+an enrolled student of UM, candidates are required to report to the University all IP
+with commercial potential. This does not mean that candidates lose their IP rights as
+their invention still belongs to them unless they have previously assigned it to another
+party. However, UM may make a claim for joint ownership if, for example, candidates
+are employed by the University to do research. In such a case, the candidates’
+contract may assign ownership to the Universiti Malaya.
+
+
+## Research Guidance :: Postgraduate Activities
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 178-181
+
+### Page 180
+»»>
+Research talk & Exchange MOU ceremony by EUREKA
+Robotics Centre, Cardiff Metropolitan
+CC Cm
+
+
+## Laboratory Regulations and Support :: Laboratory Regulations
+
+- scope_label: general
+- source_doc: Complete Handbook
+- pages: 183-183
+
+### Page 183
+4 >>>
+LABORATORY REGULATIONS
+1, Only registered users are allowed to use the facilities in the lab.
+2. Effective from 1°" april 2006, it is compulsory for users to wear the matric card in the
+lab at all times. Users who do not wear the matric cards are not allowed to enter the
+lab. Lab staff has the right to ask the user to leave upon refusing to wear or show
+his/her name tag.
+3. Ensure use of good quality of CD, thumb drives, external hard disk and virus-free
+data. The faculty reserves the right to examine before use.
+4. Users are strictly prohibited from making copies of software without the knowledge of
+the staff on duty.
+5. Users are prohibited from installing any software onto the hard disk without the
+knowledge of the staff on duty (eg; KAZAA, BitTorent, P2P software). The faculty
+reserves the right to remove such installations without any prior notice.
+6. Any hardware problems must be reported to the staff on duty. The faculty will not be
+responsible for any accidents or damage because of negligence and misuse of the
+equipment by users.
+7. Users are prohibited from playing games, chat or browse the web for pornography
+materials.
+8. Users are prohibited from bringing in friends or students from other
+faculties/universities into the lab.
+9. Users are prohibited from making noise and disturbing others. Any discussions
+should be conducted outside the lab.
+10. Smoking, bringing-in bags and foodstuffs is strictly prohibited in the lab.
+11. Users are responsible for the safekeeping of the data, hardware and cleanliness of
+other equipment in the lab including tables and chairs.
+12. Users must be properly attired inside the lab. Slippers, shorts and indecently
+dressed users are strictly prohibited.
+43. Users are prohibited to change administrator password as security reason and
+maintenance work.
+Disciplinary action will be taken by the Faculty against those who breached the
+rules and regulations mentioned above.
+(Cy Cm
+
+
+## Laboratory Regulations and Support :: Technical Problem Enquiries
+
+- scope_label: general
+- source_doc: Complete Handbook
+- pages: 184-184
+
+### Page 184
+4 >>>
+ENQUIRIES ON TECHNICAL PROBLEMS
+Users who have problems using the equipment and software can contact the technical staff
+working in the laboratory as in the table below:
+Tun Hairul Farid
+Ton Hamzah
+Micro Lab 1 (MM1) 03-79676364 tunhairul@um.edu.my
+Postgraduate Lab (ML) Nor Azura Adnan
+azura_adnan@um.edu.my
+Micro Lab 3 (MM3) Haryati Masilan 03-79676391
+haryatim@um edu my
+Mohd Annuar
+Micro Lab 6 (MM6) fee 03-79676364 | _annuar@um.edumy
+Robotic Teaching Lab Jamal Amran
+jamalamr@um.edu.my
+Operation Hours:
+8.00 a.m. —5.30 pm.
+Monday - (extended upon request according to class
+Thursday timetable)
+800 a.m.— 12.15 pm.
+Friday 2.45 p.m. — 5.30 p.m.
+(extended upon request according to class
+timetable’
+“* Computer Laboratories will be closed during maintenance work, and public holidays.
+
+
+## Undergraduate Faculty Identity :: Vision and Mission
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 187-187
+
+### Page 187
+VISION
+A global faculty impacting the world
+MISSION
+Propelling computing technology and
+producing world class leaders
+OBJECTIVES
+To sustain an outstanding faculty dedicated to excellence in
+undergraduate and postgraduate teaching, learning and research.
+To contribute towards the development of the nation through the
+production of quality research and publications.
+To provide innovative academic programs that can respond to the
+changing needs of the society.
+To produce quality graduates who are equipped with advanced
+knowledge and skills of computer science and information technology.
+
+
+## Faculty Staff :: Undergraduate Dean's Office and Department Leadership
+
+- scope_label: general
+- source_doc: Complete Handbook
+- pages: 192-199
+
+### Page 192
+STAFF
+DEAN’S OFFICE
+Coordinator Program
+Multimedia
+Head of Department
+Artificial Intelligence
+Information Systems
+Software Engineering
+Deputy Dean (Research)
+Deputy Dean (Development)
+Deputy Dean (Postgraduate)
+Deputy Dean (Student Affairs)
+Deputy Dean (Undergraduate)
+Computer System and Technology
+: Madam Mas Idayu Md. Sabri
+B.Comp.Sc. (UM), M.Sc. (Bath)
+: Dr. Muhammad Shahreeza Safiruz Kassim
+BEng
+(Electrical,
+Electronics
+and
+Information
+Engineering) (Japan), M.Sc (Artificial Intelligence)
+(UK), PhD (Southampton)
+: Dr. Asmiza Abdul Sani
+B.Comp.Sc. (UM), M.Sc. (Soft. Eng.) (UK), PhD
+(UK)
+: Dr. Hoo Wai Lam
+B.Comp.Sc. (UM), PhD (UM)
+: Associate Professor Dr. Amirrudin Kamsin
+BIT (UM), M.Sc. (Bournemouth), PhD (London)
+: Associate Professor Dr. Norisma Idris
+B.Comp.S (UM), M.Comp.Sc. (UM), PhD (UM)
+: Professor Dr. Nor Liyana Mohd Shuib
+B.Comp.Sc.(UTM), M.IT (UKM), PhD (UM)
+: Dr. Ong Sim Ying
+B.Comp.Sc. (UM), PhD (UM)
+: Associate Professor Dr. Saaidal Razalli Azzuhri
+B.Eng. (UM), M.Sc. (IT) (MUST), PhD (Queensland)
+: Dr. Erma Rahayu Mohd Faizal Abdullah
+B.Comp.Sc. (UM), M.Elect.Eng. (Oita University,
+Japan), PhD (UiTM)
+: Professor Dr. Siti Hafizah Ab Hamid
+B.Comp.Sc. (UTM), M.Sc. (Manchester), PhD (UM)
+Dean
+
+### Page 193
+STAFF
+Administration and Support Staff
+Administrative Manager (N12)
+Senior Assistant Registrar (N10)
+Assistant Registrar (N9)
+Driver (H11)
+Administrative Assistant
+(Clerical/Operational) (N1)
+General Office Assistant (N11)
+Office Secretary (N6)
+Assistant Office Secretary (N1)
+Senior Administrative Assistant
+(Clerical/Operational) (N2)
+Accountant Assistant (W5)
+Administrative Assistant (Finance) (W2)
+Administrative Assistant Officer (N5)
+: Che Mazni Sidek
+: Noor Yusrina Hashim
+: Balqis Bahari
+Nur Nadia Arshad
+Nursyahirah Mamat Yasin
+Nurul Farhana Mohd Nasir
+Siti Nurul Aisyah Zulzaidi
+: Norazleen Ramli
+: Haida Izwani Che Mahmood
+: Nur Azleen Abdul Rahim
+Siti Nor Anilawatie Muhammad
+: Mohd Afiffudin Mohd Ali
+Julianna Ariff
+Norhayati Mohd Supi
+Norkusharina Nasir
+Rohani Mohamed Arifin
+Syahrul Hasnah Ahmad
+: Zunaida Alwadood
+: Nur Hidayah Mohd Sarbini
+Nurfatehah M. Zahir
+Nurnajwa Husna Mohd Rafi
+: Azeerin Ahmad
+Al Zarinah Awang Mohktar
+Farah Nadhirah Mohd Aznam
+Norhanim Husaini
+Nur Izzati Alias
+Nurfaziela Ibrahim
+Zaleha Sumairi
+: Mohd Fareek Muhiyeddin
+Nanthini Krishnan
+: Mohd Haffes Rahim
+
+### Page 194
+STAFF
+Technical Staff
+Assistant Information Technology
+Officer (FA6)
+Assistant Engineer (JA5)
+Assistant Information Technology
+Officer (FA5)
+Senior Computer Technician (FT2)
+: Mohd Azizie Aris
+Mohd Noor Aizad Morad
+Zulkefle Kassim
+: Mohd Farhan Abdul Rahman
+: Azzyaty Razali
+Haryati Masilan
+Wan Mohd Hasanul Isyraf Wan Yusoff
+: Jamal Amran
+Mohd Annuar Ja’afar
+Tun Hairul Farid Ton Hamzah
+Nor Azura Adnan
+
+### Page 195
+STAFF
+Professor:
+Chiew Thiam Kian, B.Comp.Sc. (UM), M.Comp.Sc. (UM), PhD (Glasgow)
+Siti Hafizah Ab Hamid, B.Comp.Sc. (UTM), M.Sc. (Manchester), PhD (UM)
+Associate Professor:
+Mumtaz Begum Peer Mustafa, B.Comp.Sc. (UPM), MSE (UM), PhD (UM)
+Raja Jamilah Raja Yusof, B.Eng. (London), M.Comp.Sc. (UM), PhD (UM)
+Senior Lecturer:
+Adeleh Asemi Zavareh, B.Comp.Sc. (Iran), M.Comp.Sc. (India), PhD (UM)
+Chiam Yin Kia, B.Comp.Sc. (UM), M.Sc. (Info. Tech.) (UM), PhD (Australia)
+Hema Subramaniam, BSc (IT) (UNISEL), M.Comp.Sc. (UNISEL), PhD (UPM)
+Siti Nurliana Jamalai@Jamali, B.Comp.Sc.Software Engineering (MSU), M.Comp.Sc.Software
+Engineering (UPM), PhD (UPM)
+Mohamad Hazim Md Hanif, B.Comp.Sc. (UM), M.Comp.Sc. (UM), PhD (Imperial)
+Nazean Jomhari, B.Sc. (UKM), M.Sc. (Essex), PhD (Manchester)
+Nur Nasuha Mohd Daud, B.Comp.Sc. (UM), PhD (UM)
+Ong Sim Ying, B.Comp.Sc. (UM), PhD (UM)
+Su Moon Ting, B.Comp.Sc. (UPM), M.Comp.Sc. (UPM), PhD (Auckland)
+Uzair Iqbal, B.SE (Pakistan), M.SE (Pakistan), PhD (UM)
+Head of Department:
+Asmiza Abdul Sani, B.Comp.Sc. (UM), M.Sc. (Soft. Eng.) (UK), PhD (UK)
+DEPARTMENT OF SOFTWARE ENGINEERING
+
+### Page 196
+STAFF
+Professor:
+Ir.Chan Chee Seng, B.Eng. (MMU), M.Sc. (Portsmouth), PhD (Portsmouth)
+Loo Chu Kiong, B.Mech.Eng. (UM), PhD (USM)
+Associate Professor:
+Ts.Aznul Qalid Md Sabri, B.Comp.Sc. (UM), M. (Vision & Robotics) (Heriot-Watt), M. (Robotic)
+(Uni. De Bourgogne), PhD (France)
+Norisma Idris, B.Comp.Sc. (UM), M.Comp.Sc. (UM), PhD (UM)
+Senior Lecturer:
+Liew Wei Shiung, M.Eng (UM), B.Eng (MMU), PhD (UM)
+Lim Chee Kau, B.Sc. (USM), M.Comp.Sc. (UM), PhD (UM)
+Nurul Japar, B.Comp.Sc (UM), PhD (UM)
+Saw Shier Nee, B.Bio.Eng. (UM), PhD (NUS)
+Unaizah Hanum Obaidellah, B.Comp.Sc. (UM), M.Comp.Sc. (UM), PhD (UK)
+Woo Chaw Seng, B.Comp.Sc. (UM), M.Comp.Sc. (UM), PhD (Australia)
+Zati Hakim Azizul Hasan, B.Comp.Sc. (UM), M.Comp.Sc. (UM), PhD (New Zealand)
+Uzair Istiaq, B.Comp.Sc (Pakistan), M.Comp.Sc (Pakistan), PhD (UM)
+Zainab Malik, B.Comp.Sc (Pakistan), M. Phil (Pakistan), PhD (UTM)
+Dr Narsimlu Kemsaram, B.Tech (India) M. Tech (India), PhD (India)
+Honorary Professor
+Datin Sameem Abdul Kareem, B.Sc. UM (1986), M.Cs., University of Wales, UK (1992), PhD,
+UM (2002)
+Head of Department:
+Muhammad Shahreeza Safiruz Kassim, BEng (Electrical, Electronics Engineering)
+(Japan), M.Sc (Artificial Intelligence) (UK), PhD (Southampton)
+DEPARTMENT OF ARTIFICIAL INTELLIGENCE
+
+### Page 197
+STAFF
+Lecturer:
+Emran Mohd Tamil, B.Eng. (UTM), M.Sc. (UiTM)
+Fazidah Othman, B.Comp.Sc. (UTM), M.Sc. (UTM)
+Noorzaily Mohamed Noor, B.Sc. (UM), M.Comp.Sc. (UM)
+Professor:
+Ts. Miss Laiha Mat Kiah, B.Comp. Sc. (UM), M.Sc. (London), PhD (London)
+Ts. Nor Badrul Anuar Juma’at, B.Comp.Sc. (UM), M.Comp.Sc. (UM), PhD (UK)
+Ts. Rafidah Md Noor, BIT (UUM), M.Sc. (UTM), PhD (Lancaster)
+Mohd Yamani Idna Idris, B.Eng. (UM), M.Comp.Sc. (UM), PhD (UM)
+Por Lip Yee @ Por Khoon Sun, B.Comp.Sc. (UM), M.Comp.Sc. (UM), PhD (UM)
+Associate Professor:
+Ts. Ismail Ahmedy, Dip.Comp.Sc. (UTM), B.Sc. (Computer) (UTM), M.Sc. (Computer Science)
+(Queensland), PhD (UTM)
+Ang Tan Fong, BIT (UM), M.Comp.Sc. (UM), PhD (UM)
+Ling Teck Chaw,B.Sc. (UM), M.Comp.Sc. (UM), PhD (UM)
+Rosli Salleh, B.Comp.Sc. (UM), M.Sc. (Salford), PhD (Salford)
+Tey Kok Soon,B.Eng. (Electrical) (UM), PhD (UM)
+Saaidal Razalli Azzuhri, B.Eng. (UM), M.Sc. (IT) (MUST), PhD (Queensland)
+Senior Lecturer:
+Honorary Professor
+Abdullah Gani, B.Phil. (Hull University), M.Sc. (Information Management) (Hull University), PhD
+(University of Sheffield)
+Head of Department:
+Amirrudin Kamsin, BIT(UM), M.Sc. (Bournemouth), PhD (London)
+DEPARTMENT OF COMPUTER SYSTEM AND TECHNOLOGY
+Bryan Raj A/L Peter Jabaraj, B.Comp.Sc. (UM), PhD (UM)
+Muhammad Faiz Mohd Zaki, B.Comp.Sc. (UM), M.Sc (London), PhD (UM)
+Muhammad Nur Firdaus Sahran, B.Comp.Sc. (UM), PhD (UM)
+Burhan Ul Islam Khan, BTech (Pulwama), M.Sc. (Computer and Information Engineering) (IIUM),
+PhD (IIUM)
+
+### Page 198
+STAFF
+Lecturer:
+Hannyzzura Pal @ Affal, B.Comp.Sc. (UM), M.Sc. (London)
+Mas Idayu Md. Sabri, B.Comp.Sc. (UM), M.Sc. (Bath)
+Nornazlita Hussin, B.Comp.Sc. (UM), M.Sc. (Bath)
+Professor:
+Ts.Ainuddin Wahid Abdul Wahab, B.Comp.Sc. (UM), M.Comp.Sc. (UM), PhD (UK)
+Associate Professor:
+Amirrudin Kamsin, BIT (UM), M.Sc. (Bournemouth), PhD (London)
+Mohamad Nizam Ayub, B.Comp.Sc. (UM), M.Sc. (Edinburgh), PhD (UK)
+Nor Aniza Abdullah, B.Comp.Sc. (UM), M.Sc. (London), PhD (Southampton)
+Senior Lecturer:
+Nurul Fazmidar Mohd Noor, B.Comp.Sc. (UM), M.Sc. (Liverpool), PhD (UK)
+Rasha Ragheb Attaallah, B.Comp Edu (Al Aqsa), M.Sc. (Islamic university Gaza), PhD (UM)
+Suzan Jabbar Obaiys, B.Sc. (Iraq), M.Sc. (UPM), PhD (UPM)
+MULTIMEDIA UNIT
+Coordinator Programme:
+Mas Idayu Md. Sabri, B.Comp.Sc. (UM), M.Sc. (Bath)
+
+### Page 199
+STAFF
+Professor:
+Nor Liyana Mohd Shuib, B.Comp.Sc. (UTM), M.IT (UKM), PhD (UM)
+Teh Ying Wah, B.Sc. (Oklahoma), M.Sc. (Oklahoma), PhD (UM)
+Ts. Vimala A/P Balakrishnan, B.Comp.Sc. (USM), M.Sc. (Comp.Sc.) (USM), PhD (MMU)
+Associate Professor:
+Ts.Sri Devi A/P Ravana, BIT (UKM), MSE (UM), PhD (Melbourne)
+Azah Anir Norman, BIT (UKM), M.Sc. (London), PhD (UM)
+Norjihan Abdul Ghani, BIT (UUM), MIT (Sc.) (UKM), PhD (UTM)
+Kasturi Dewi A/P Varathan, BIT (Uniten), M.Comp.Sc (MIS) (UM), PhD (UKM)
+Maizatul Akmar Ismail, BIT (UM), M.Sc. (UPM), PhD (UM)
+Suraya Hamid, BIT (UKM), MIT (UKM), PhD (Melbourne)
+Tutut Herawan, B.Ed (Ahmad Dahlan University), M.Sc. (Gadjah Mada University), PhD (UTHM)
+Senior Lecturer:
+Ts. Mohd Shahrul Nizam Bin Mohd Danuri, BSc (USM), M.Sc (UKM), PhD (UITM)
+Riyaz Ahamed Ariyaluran Habeeb, B.E (CS) (Sathyabama University), MSE (UM), PhD (UM)
+Head of Department:
+Hoo Wai Lam, B.Comp.Sc. (UM), PhD (UM)
+DEPARTMENT OF INFORMATION SYSTEMS
+
+
+## Undergraduate Programmes :: Programmes Offered
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 200-200
+
+### Page 200
+PROGRAMMES OFFERED
+There are six (6) programmes offered under the Computer Science as follows:
+1.Bachelor of Computer Science (Computer System and Network)
+2.Bachelor of Computer Science (Artificial Intelligence)
+3.Bachelor of Computer Science (Information Systems)
+4.Bachelor of Computer Science (Software Engineering)
+5.Bachelor of Computer Science (Multimedia Computing)
+6.Bachelor of Computer Science (Data Science)
+
+
+## Shared Undergraduate Curriculum :: University Courses
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 225-227
+
+### Page 226
+GIG1003,
+BASIC ENTREPRENEURSHIP ENCULTURATION
+Credit: 2
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the basic concepts of entrepreneurship.
+2. Producing — creative. © and_—_—innovative
+entrepreneurial ideas.
+3. Develop a business plan framework.
+‘Synopsis of Course Content
+The course will attempt to inculcate the basic
+elements of entrepreneurship in the students.
+initiatives are taken to open their minds and
+motivate the entrepreneurial spirit in this potential
+target group. The course encompasses theory and
+development of entrepreneurship, factors affecting
+entrepreneurship, entrepreneurship development in
+Malaysia, ethics of entrepreneurship, creativity and
+innovation in entrepreneurship and developing
+business plans. This course also incorporates a
+direct exposure to entrepreneurial mindset, skills
+and competencies.
+Assessment Methods
+Continuous Assessment: 100%
+GIG1012
+PHILOSOPHY AND CURRENT ISSUES
+Credit
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain current issues based on philosophy, the
+Philosophy of National Education and the Rukun
+Negara.
+2. Explain current issues based on the main of
+thoughts from the various streams of philosophy.
+3. Explain current issues through a comparative
+perspective of philosophy as a basis for
+establishing inter-cultural dialogue.
+‘Synopsis of Course Content
+This course covers philosophical relations with the
+Philosophy of National Education and Rukun
+Negara. The use of philosophy as a tool to purify
+the culture of thought in life through the arts and
+methods of thinking and human concepts. The main
+topics in philosophy are epistemology, metaphysics
+and ethics discussed in the context of current
+issues, Emphasis is given to philosophy as a basis
+for fostering inter-cultural dialogue and fostering
+one's values. At the end of this course students will
+be able to see the disciplines of science as one
+comprehensive body of knowledge and related to
+each other.
+Assessment Methods
+Continuous Assessment: 70%
+Final Examination: 30%
+GIG1013
+APPRECIATION OF ETHICS AND CIVILISATIONS
+Credit; 2
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the ethical
+civilizations.
+2. Compare systems, levels of development, social
+progress and culture across nationalities.
+3. Discuss contemporary issues related to
+economics, politics, the social, the environment
+and culture from the perspective of ethics and
+civilization
+concepts of different
+‘Synopsis of Course Content
+This course discusses ethical concepts from
+different civilization perspectives. It aims to identify
+the systems, developmental stages, progress and
+culture of a nation in strengthening social cohesion.
+In addition, discussions on contemporary issues in
+the economic, political, social, cultural and
+environmental aspects from an ethical and civil
+perspective can produce students who are morally
+and professionally sound. The application of
+appropriate High Impact Education Practices
+(HIEPs) is used in the delivery of this course. At the
+end of this course students will be able to relate
+ethics and civic-minded citizenship.
+Assessment Methods
+Continuous Assessment: 70%
+Final Examination: 30%
+GiG1017
+BASIC MALAY LANGUAGE
+Credit: 2
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Read syllables, words, phrases or expressions
+in Malay correctly.
+2, Demonstrate spoken and written skills using
+simple Malay.
+3. Write short paragraphs on selected topics using
+simple language styles.
+‘Synopsis of Course Content
+
+### Page 227
+This course emphasises mastering basic skills in
+Malay for Intemational students enrolled in the
+undergraduate study programmes, The course
+includes four skills, which are pronunciation and
+‘speaking; listening, reading and writing in Malay for
+basic communication. Emphasis is given to oral and
+written exercises.
+Assessment Methods
+Continuous Assessment: 60%
+Final Examination: 40%
+
+
+## Shared Undergraduate Curriculum :: Faculty Core Courses
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 228-230
+
+### Page 229
+WIx1001
+COMPUTING MATHEMATICS |
+Credit: 3
+Course Pre-requisite(s): None
+Medium of instruction: English
+Learning Outcomes
+1. Identify fundamental concepts and terminology
+in computing mathematics.
+2. Solve mathematical proofs using the
+fundamental mathematics concepts.
+3. Apply various computing mathematics.
+techniques to solve problems.
+Synopsis of Course Content
+This course covers mathematics and its
+applications in computer science. Topics include
+number theory, sets, relations and functions, logic,
+graphs and trees, matrices, vector and
+combinatorics. It also covers _ mathematical
+applications in computer science (such as
+applications of sets and functions in program
+semantics, logic in program specification,
+equivalence and order relations in program
+complexity, graphs and trees in game theory,
+matrices in graphics, number theory in secure
+communication).
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WIx1002
+FUNDAMENTALS OF PROGRAMMING
+Credit: 5
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Define the steps of problem solving in
+programming.
+2. Rewrite programs that contain errors.
+3. Develop programs based on principles of
+object-oriented.
+Synopsis of Course Content
+This course covers problem solving and the
+fundamental of programming. These include
+problem solving techniques, the basic structure of
+computer program, the fundamental concepts of
+object-oriented programming, data types and
+operations, selection control structures i.e. if and
+switch, repetition control structures i.e. for, while,
+do-while, function, array, string, text file, and
+programming practice.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wix1003.
+COMPUTER SYSTEMS AND ORGANIZATION
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Describe the basic computer organization and
+logic design.
+2. Explain the basic computer systems design,
+combinational circuit and sequential logic.
+3. Interpret the basic concepts of computer
+systems operation,
+Synopsis of Course Content
+This course covers the introduction to computer
+systems and organization which includes number
+system, Boolean Algebra, basic logic gates,
+function simplification, combinational circuit
+latches and flip-flop, sequential circuit and
+addressing mode. This course also gives an
+introduction to processor system
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wix2001
+‘THINKING AND COMMUNICATION SKILLS
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Apply communication and thinking skills in
+various environments.
+2. Plan and implement an entrepreneur activity.
+3. Demonstrate an active, committed and ethical
+role in course and group activities.
+‘Synopsis of Course Content
+This course will cover topics to develop effective
+communication and critical thinking. Topics for
+communication skill include verbal and non-verbal
+communication skills, listening skills, presentation
+skills and barriers to communication. Topies taught
+for the latter include techniques to clarify, analyze
+and evaluate arguments, logical fallacies, problem
+solving and decision making. Additionally, methods.
+to find, evaluate and use information sources
+correctly will be explained. The teaching and
+leaming methods for the course able develop
+individual, leadership and teamwork skills.
+Assessment Methods
+Continuous Assessment: 70%
+Final Examination: 30%
+
+### Page 230
+wix2002
+PROJECT MANAGEMENT
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Elaborate the purpose and importance of
+project management from the perspectives of
+planning, tracking and completion of project.
+2. Identify ‘appropriate techniques. to estimate
+project time and costs
+3. Perform @ project to track project schedule,
+expenses, and resources with the use of
+suitable project management tools.
+Synopsis of Course Content
+This course introduces the fundamental of
+management concepts, explains topics _on
+‘organizational structures, project planning,
+techniques for project time and costs estimation
+risk management, the various issues involved in
+the management of project _ personnel,
+measurement and evaluation of project progress
+and performance, and project control. This course
+also covers project aucit and closure,
+Assessment Methods
+Continuous Assessment: 70%
+Final Examination: 30%
+
+
+## Shared Undergraduate Curriculum :: Programme Core Courses
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 231-239
+
+### Page 231
+PROGRAMME
+CORE COURSES
+COURSE INFORMATION
+Bachelor of Computer Science (Computer System and Network)
+Bachelor of Computer Science (Artificial Intelligence)
+Bachelor of Computer Science (Information Systems)
+Bachelor of Computer Science (Software Engineering)
+Bachelor of Computer Science (Multimedia Computing)
+Bachelor of Computer Science (Data Science)
+
+### Page 232
+Wiato01
+INFORMATION SYSTEMS
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain basic information systems concepts
+and principles.
+2. Describe the ecosystem in which information
+systems are employed.
+3, Determine societal and ethical impacts of
+information systems.
+Synopsis of Course Content
+This course covers the following topics: Overview
+of Information System (IS) (Introduction to IS, I$ in
+organisation): Information Technology Concepts in
+IS; Managing Data and Information; Type of
+Business Information Systems; Knowledge
+Management and Specialized information Systems:
+IS Stakeholders; Planning, Developing, Managing
+and Evaluating IS; Securing Information Systems:
+IS in Society, Business and Industry (Security Issue
+and Privacy, Ethics and IS); and Case study on IS
+in organization
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WiA1002
+DATA STRUCTURE
+Credit: 5
+Course Pre-requisite(s): WIX1002
+Medium of Instruction: English
+Learning Outcomes
+1. Define the data structure ADT operations.
+2. Implement the data structure _ internal
+operations.
+3, Develop general-purpose, reusable data
+structures ‘that implement one or more
+abstractions.
+‘Synopsis of Course Content
+For any type of query possible on digital data, there
+is @ corresponding data structure supporting it. A
+data structure can be linear such as array, stack,
+queue, linked list etc., and non-inear such as
+graph, trees etc. A central goal in this course is to
+emphasize object-oriented view of data structures
+including encapsulation and abstract data types
+(ADTs), and, to lear how these data structures
+work internally by manipulating arrays, lists and
+pointers to perform searching, insertion, deletion,
+traversing and other operations.
+Assessment Methods
+Continuous Assessme!
+Final Examination: 50%
+50%
+‘WIA1003
+COMPUTER SYSTEM ARCHITECTURE
+‘Course Pre-requisite(s): WIX1003
+Medium of Instruction: English
+Learning Outcomes
+1. Identify the concept of top-down approach to
+show the computer system architecture,
+2. Use basic operation and instruction set
+architecture.
+3. Explain the difference between computer
+organization and computer architecture,
+‘Synopsis of Course Content
+This course covers the introduction to computer
+architecture which includes global system structure,
+instruction sets, addressing mod, fundamental
+processor execution technique, pipelining, RISC
+and CISC design, memory hierarchy, cache
+memory, bus interconnection, I/O system,
+multiprocessing system and current topic in
+computer architecture,
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+‘WIA1005
+NETWORK TECHNOLOGY FOUNDATION
+Credit: 4
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Describe the protocols, _ architecture,
+‘components, addressing and operations in a
+network,
+2. Explain basic routing and switching concepts.
+3. Solve switching and routing problems in a
+network,
+Synopsis of Course Content
+This course is designed to provide students with the
+fundamental concepts of computer networking
+which include TCP/IP model, IPv4 and IPvé
+addressing, routing and switching. This course will
+examine several aspects of networking such as
+VLAN, ACL, DHCP and NAT. This course also
+emphasis on practical exercises in routing and
+switching.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+
+### Page 233
+‘WIA1006
+MACHINE LEARNING |
+Course Pre-requisites): None
+Medium of Instruction: English
+Learning Outcomes
+Describe the fundamental issues and
+challenges of machine learning,
+2. Understand the underlying _ mathematical
+relationships within and cross machine learning
+algorithms and the paradigms of supervised
+and unsupervised learning.
+3. Design various machine leaming algorithms in
+a range of real-world applications.
+‘Synopsis of Course Content
+This course will introduce the field of Machine
+Learning, focusing on the core concepts of
+supervised and unsupervised learning. In
+supervised learning we will discuss algorithms
+Which are trained on input data labelled with a
+desired output, for instance an image of a face and
+the name of the person whose face itis and learn a
+function mapping from the input to the output,
+Unsupervised leaming aims to discover latent
+structure in an input signal where no output labels
+are available, an example of which is grouping
+webpages based on the topics they discuss.
+Students will learn the algorithms which underpin
+many popular Machine Leaming techniques, as
+well as developing an understanding of the
+theoretical relationships between these algorithms.
+The practical will concern the application of
+machine learning to a range of reabworld
+problems
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WiA1007
+INTRODUCTION TO DATA SCIENCE
+Credit: 3
+Course Pre-requisites); None
+Medium of Instruction: English
+Learning outsomes
+Explain the key concepts relevant to data
+science, including all processes in the data
+science life cycle and data science applications
+in real-world
+2. Determine suitable tools, technologies and the
+core algorithms underlying an end-to-end data
+science workflow, including the experimental
+design, data collection, mining, analysis, and
+presentation of information derived from
+datasets.
+3. Interpret the ethical implications on the use of
+data and technologies in data science process.
+‘Synopsis of Course Content
+The course is designed to help the student learn
+fundamental concepts of data science. It covers
+what, when, who, where why and how (SW 1H) of
+data science in the era of big data. Also
+encompass, the life cycle of data science from data
+preparation, data processing, data cleansing and
+integration, to data analysis and visualization of
+data in data-criven decision making. The role of
+data scientist, the knowledge and skills
+required are also presented. Machine learning
+algorithms and statistical models are included.
+Diverse technologies, programming languages es
+well as tools in data science are discussed.
+Assessment Methods
+Continuous Assessment: 60%
+Final Examination: 40%
+‘wiA1008
+FUNDAMENTAL OF MULTIMEDIA
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Describe the principles of each element of a
+multimedia system.
+2. Evaluate the design of a multimedia application
+and provide recommendations for improvement
+3. Develop @ multimedia application development
+through multiple elements creation and
+manipulation using appropriate multimedia
+editing and authoring tools,
+‘Synopsis of Course Content
+During the course, students will be introduced to
+the main elements of the multimedia system
+including texts, images and graphics, audio, video
+and animation. Students will be taught the process
+of editing multimedia elements using editing tools
+such as Adobe Photoshop, illustrator, Animate,
+Rush, and Audacity, Students will also be exposed
+to issues related to data compression, security, and
+current multimedia technology.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+
+### Page 234
+wia2001
+DATABASE
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Describe the basic concepts in database,
+2. Design a database system for an application or
+‘small business.
+3. Implement the database design using @
+Database Management System (DBMS),
+Synopsis of Course Content
+This course introduces the concepts of file-based
+systems vs DBMS. It provides students with the
+knowledge of database architecture, models, and
+processes necessary for using, designing, and
+implementing database systems and ap
+Students will have hands on sessions to use DBMS
+and write SQL commands. Database applications
+will be developed based on case studies.
+Transaction management topics and other issues
+related to database management system are also
+discussed,
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wia2002
+SOFTWARE MODELLING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+Explain the concepts of software modelling,
+2 Consiet’ sofware model using the UML
+notation
+3. Use a UML CASE tool to produce and manage
+software models.
+‘Synopsis of Course Contents
+This course covers object-oriented modelling
+concepts in system design using Unified Modelling
+Language (UML). Topies include basic concepts of
+modelling in system design, key differences
+between the structured and objectriented
+paradigm, design of a software system using
+structural and behavioral diagrams, use of an
+object-oriented case tool to construct various UML
+diagrams and generate source codes, consistency
+checking of UML model.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WIA2003
+PROBABILITY AND STATISTICS
+Credit: S
+Course Pre-requisite(s): None
+Medium of Instructi
+: English
+Learning Outcomes
+1. Explain probabilistic and statistical concepts.
+2. Use basic probabilistic and statistical concepts.
+3. Employ the appropriate statistical tests to
+analyze data.
+‘Synopsis of Course Content
+This course provides an introduction to probability
+and statistics concepts which includes Introductory
+Notions, Conditional Probability, Bayes Theorem,
+Binomial and Poisson Distributions, among others
+As for statistics, the course aims to develop
+students’ ability to describe, explore and analyze
+data (both descriptive and inferential statistics)
+using a statistical package (e.g., SAS/SPSS),
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WiA2004
+OPERATING SYSTEMS
+Credit: 4
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+ist the basic concept of operating systems,
+2. Elaborate the eta on memory, device and
+file management for early systems and current
+systems.
+3. Explain the criteria on processor and process
+management and know how to handle it.
+‘Synopsis of Course Content
+This course covers basic concepts of operating
+systems which includes memory management in
+early and recent systems, processor and process
+managements, concurrent process, deadlock, and
+starvation. This course also provides insights into
+device, file and system management, as well as
+examples of operating systems.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+
+### Page 235
+WwIA2005
+ALGORITHM DESIGN AND ANALYSIS
+Credit: 4
+Course Pre-requisite(s):
+WIA1002 - Data Structure
+Medium of Instruction: English
+Learning Outcomes
+1. Describes major algorithms related to advanced
+data structures and time complexity,
+2. Implement important algorithm design
+paradigms.
+3, Assess the performance of algorithms,
+Synopsis of Course Content
+This course introduces students to the analysis and
+design of computer algorithms. Students will learn
+basics design techniques, important classical
+algorithms and advanced data structures, and their
+implementation in the moder programming
+environment. Students are exposed to a few
+algorithms design paradigm.
+Assessment Method
+Continuous Assessment: 70%
+Final Examination: 30%
+WIA2006
+‘SYSTEM ANALYSIS AND DESIGN
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Identify various concepts, principles, and stages
+of computer-based information systems
+analysis, modelling, and design.
+2, Review of the groups of people involved in
+systems development and the different
+methods, tools, and techniques used in
+systems analysis, modelling and design.
+3. Apply concepts and skills to develop an
+information system.
+Synopsis of Course Content
+This course deals with process of collecting and
+interpreting facts, identifying the problems, and
+decomposition of a system into its components and
+planning the development of information systems
+through understanding and specifying in detail what
+a system should do and how the components of
+the system should be implemented and work
+together. In addition, this course also deals with the
+concepts, skills, methodologies, techniques, tools,
+and perspectives essential for systems analysts
+System analysts solve business problems through
+analyzing the requirements of information systems
+and designing such systems by applying analysis,
+modelling, and design techniques. The practical
+component of this course is object-oriented design
+and use-case driven, requiring students to go
+through the steps of system analysis, modelling
+and design to solve a real-life business problem.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+‘wiA2007
+MOBILE APPLICATION DEVELOPMENT
+Credit: 4
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain various categories of mobile
+applications, its framework, lifecycle and its
+relevant User interface components, services
+and libraries
+2. Analyze the appropriate functionalities and
+sketches for mobile application based on its
+intended purposes and users.
+3. Develop the mobile applications using suitable
+components, services, or libraries, with
+database utilization,
+‘Synopsis of Course Content
+This course provides an understanding on the
+categories, development framework and lifecycle of
+typical mobile applications. Besides, relevant GUI
+components and its event handling, services and
+libraries are introduced, including location-aware
+service, audio, etc. This course also gives practical
+hands-on on mobile application development with
+database connection, by considering users
+hardware and software requirements as a whole.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+~ wia2008 ~ ”
+ADVANCED NETWORK TECHNOLOGY
+Credit: 4
+Course Pre-requisite(s): WIA1005
+Medium of Instruction: English
+Learning Outcomes
+4. Identify the architecture, components, and
+‘operations of routers and switches in complex
+networks.
+2. Explain the issues, philosophies and protocols
+involved in managing a local and wide area
+network infrastructure.
+3. Solve the common problems of routers and
+switches in IPv4 and IPV6 networks.
+
+### Page 236
+‘Synopsis of Course Content
+This course is designed to provide students with
+the overall concept and needs of network
+technologies in advance level. This course will
+examine several aspects of networking such as
+OSPF, EIGRP, STP, PPP and VPN in IPv4 and
+IPv6 networks. This course also emphasis on
+practical exercises by introducing a range of
+network technologies and protocols used in a
+network.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WIA2009
+DIGITAL DESIGN AND HARDWARE
+DESCRIPTION LANGUAGE
+Credit: 3
+Course Pre-requisite(s): WIA1003 & WIX1003
+Medium of Instruction: English
+Learning Outcomes
+4. Explain the basic components of computer
+digital development and how those components
+functioning.
+2. Discuss cigital design issues
+3. Develop digital circuit using systematic design
+methods using HDL or any Electronic Design
+‘Automation ~ (EDA) and Electronic
+Computer-Aided Design (ECAD) equipment.
+‘Synopsis of Course Content
+This course consists of basic introduction to digital
+design, combinational logic design principle and
+Practice, sequential logic design principle and
+practice, memory, CPLD and FPGA, design
+method using HDL and case stucies.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WIA2010
+HUMAN COMPUTER INTERACTION
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the ways human factors and cognitive
+models influence aspects of interface design
+2. Apply design principles, guidelines, patterns
+and visual design elements to the interface
+design and selected interface construction tools
+for the implementation of interactive systems.
+3. Evaluate interactive systems (websites, travel,
+or game apps), with a strong adoption of
+user-centric design
+‘Synopsis of Course Content
+This course covers both human factors and the
+technical methods for the design and evaluation of
+interactive systems, where it is structured within
+four main topics: overview of HCI, essential
+interaction design principles, user interface
+development process and interface design and
+programming. Overview of HCI introduces human,
+computer and interactions; user _ interfaces:
+usability, user experience (UX) and design thinking.
+Interfaces development process includes topics on
+iterative design, user-centered design, design
+discovery, design exploration and evaluation of
+user interfaces. Interface design and programming
+include topics on visual information design, forms
+design, interface design pattems, prototyping and
+construction tools, and responsiveness issue.
+Three types of applications are covered: Graphical
+User Interfaces, Web and Mobile Devices.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+‘wiA3001
+INDUSTRIAL TRAINING
+Credit: 12
+Course Pre-requisite(s):
+Taken all Faculty and Programme Core Courses
+(except Academic Project | and Academic Project
+I).
+Medium of Instruction: English
+Learning Outcomes
+. Apply operation, management, and
+development processes at workplace.
+2. Identify the problems faced and lessons leamt
+at the workplace.
+3. Use appropriate systems and technologies in
+the tasks at workplace.
+4. Demonstrate professional ethics at workplace
+to knowledge and skills acquired at
+‘Synopsis of Course Content
+This course requires a student to undergo industrial
+training at an organization offering internship
+related to the student's field of study. The student
+records his/her daily activities at the workplace in a
+logbook. The student also prepares a final report
+about his/her industrial training.
+Assessment Methods
+Continuous Assessment: 100%
+
+### Page 237
+wiA3002
+ACADEMIC PROJECT I
+Credit: 3
+Course Pre-requisite(s):
+Pass all Faculty and Programme Core courses
+except for industrial Training.
+Medium of Instruction: English
+Learning Outcomes
+1. Identify solution approach that is suitable for the
+stated problem
+2. Conduct suitable requirement gathering, system
+analysis and design techniques.
+3. Present project proposal paper.
+Synopsis of Course Content
+This course covers the activities including problem
+identification, literature review, data collection,
+writing and presenting project proposals.
+WIE2003
+INTRODUCTION TO DATA SCIENCE
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the key concepts relevant to data
+science, including all processes in the data
+science life cycle and data science applications
+in real-world
+2. Determine suitable tools, technologies and the
+core algorithms underlying an end-to-end data
+science workflow, including the experimental
+design, data collection, mining, analysis, and
+presentation of information derived from
+datasets,
+3. Interpret the ethical implications on the use of
+data and technologies in data science process.
+Assessment Methods
+Continuous Assessment: 100%
+‘Synopsis of Course Content
+The course is designed to help the student leam
+fundamental concepts of data science. It covers
+What, when, who, where, why and how (SW 1H) of
+data science in the era of big data. Also
+‘encompass, the life cycle of data science from data
+preparation, data processing, data cleansing and
+integration, to data analysis and visualization of
+data in data-driven decision making. The role of
+data scientist, the knowledge and skills required are
+also presented. Machine learning algorithms and
+statistical models are included. Diverse
+technologies, programming languages as well as
+tools in data science are discussed.
+‘WIA3003
+ACADEMIC PROJECT II
+Credit: 5
+Course Pre-requisite(s):
+Pass all Faculty and Programme Core courses
+except for Industrial Training.
+Medium of Instruction: English
+Assessment Method
+Continuous Assessment: 60%
+Learning Outcomes
+: Final Examination:40%
+|. Develop a system based on the solution
+approach and method identified
+2. Present the implemented project
+3. Implement a system with ethics and
+professionalism.
+WID3006
+MACHINE LEARNING
+Synopsis of Course Content
+This course covers research activities including
+system analysis. and design, _system
+implementation, testing and evaluating the
+developed system, project presentation and writing
+an academic report
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Assessment Method Learning Outcomes
+Continuous Assessment: 100% 1. Explain the concepts and techniques for
+supervised learning, semi-supervised learning
+and unsupervised learning
+2. Use the appropriate machine learning
+techniques for given sample datasets.
+3. Apply practical solutions to solve common
+problems in machine learning
+‘Synopsis of Course Content
+This course covers a broad understanding of the
+field of machine learning and statistical pattem
+recognition. Topics include classification and linear
+
+### Page 238
+regression, Bayesian network, decision trees,
+SVMs, statistical leaming method, unsupervised
+learning and reinforcement learning
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+‘WIH3001
+DATA SCIENCE PROJECT
+Credit: 3
+Course Pre-requisite(s); None
+Medium of instruction: English
+Learning Outcomes
+Define the problem background,
+Determine the objectives of project.
+Identify suitable solution approaches for the
+stated problem.
+4, Review literature relevant to the stated problem.
+5. Conduct data gathering using suitable
+techniques,
+8. Develop a prototype of the proposed solution
+7. White a project report
+Synopsis of Course Content
+This course covers the following research activities
+including problem and objectives. identification:
+literature review; data collection, prototype
+development, report writing and project
+presentation.
+Assessment Method
+Continuous Assessment: 100%
+‘wiH3002
+DATA SCIENCE INDUSTRIAL TRAINING
+Credit: 14
+Course Pre-requisite(s):
+Taken all Faculty and Programme Core Courses.
+Medium of Instruction: English
+Learning Outcomes
+1. Understanding real-world case
+studies/problems that require data science
+solutions in industry.
+2. Use appropriate data science technologies in
+tasks at workplace.
+3. Apply data science industrial experience in one
+of more industry-based projects.
+Synopsis of Course Content
+This course requires a student to acquire date
+science industrial experience at an organisation
+offering internship related to data science field of
+study. The student records his/her daily
+experiences at the workplace in a logbook, The
+student also prepares a final report about his/her
+data science industrial experiences,
+Assessment Method
+Continuous Assessment: 100%
+‘WIH3005
+PROFESSIONAL DEVELOPMENT
+Credit: 2
+Course Pre-requisite(s):
+None
+Medium of Instruction: English
+Learning Outcomes
+1. Differentiate various principles and practices of
+professional development within the workplace
+2. Demonstrate effective communication and
+teamwork skills in a professional environment.
+3. Demonstrate ethical and professional behavior
+‘workplace settings
+‘Synopsis of Course Content
+This Professional Development module equips
+students for success by emphasizing vital
+management, social skills, communication, and
+ethics, It addresses stakeholder management,
+project initiation, critical thinking, professional
+ethics, and communication, enhancing skills in
+report writing, team building, technical aspects,
+lifelong leaming, and conflict resolution. Students
+will develop comprehensive abilities essential for
+effective project management and career
+advancement, ensuring they are prepared for
+real-world challenges in diverse professional
+settings.
+Assessment Method
+Continuous Assessment: 100%
+WIH3006
+DATA SCIENCE AND APPLICATION
+Credit: 5
+Course Pre-requisite(s):
+Taken all Faculty and Programme Core Courses.
+Medium of Instruction: English
+Learning Outcomes
+1. Apply the fundamental concepts and
+methodologies of data science in
+workplace settings.
+2. Adapting data science solutions to
+real-world problems using relevant tools
+and technologies.
+3. Explain the impact of data science
+applications on business processes and
+decision-making.
+
+### Page 239
+Synopsis of Course Content
+This course provides a comprehensive introduction
+to the fundamental concepts and methodologies
+that underpin the field of data science. Students will
+gain a deep understanding of essential data
+science principles and learn how to apply various
+tools and technologies to solve real-world
+problems. The course emphasizes _ practical
+applications, equipping students with the skills
+needed to recommend appropriate data science
+methods for diverse scenarios. Additionally,
+students will explore the significant impact of data
+science applications on business processes and
+decision-making, enabling them to evaluate and
+nhance business strategies through data-driven
+insights. This course is designed to bridge the gap
+between theoretical knowledge and practical
+implementation, preparing students for successful
+careers in data science and analytics.
+Assessment Method
+Continuous Assessment: 100%
+WIH3007
+INDUSTRIAL SOLUTION DEVELOPMENT
+Credit: 5
+Course Pre-requisite(s):
+None
+Medium of Instruction: English
+Learning Outcomes
+1. Demonstrate problem-solving skills by
+engaging in industrial projects.
+2. Develop industrial solutions, from problem
+identification to solution deployment using data
+science pipelines.
+3. Develop the ability to work collaboratively with
+industry professionals and stakeholders
+through continuous learning,
+Synopsis of Course Content
+This course provides a comprehensive framework
+for applying theoretical knowledge and technical
+skills acquired throughout the data science program
+to real-world industrial problems. Students will solve
+industry-related problems with data science, starting
+by defining the business objective and collecting
+relevant data. Next, prepare and clean the data,
+followed by conducting exploratory analysis to
+identify patterns. Further, build and evaluate
+Predictive models, and select the best performing
+‘one. The model will be deployed into production
+Finally, communicate insights to stakeholders with
+clear visualizations and reports for actionable
+decision-making. Students will collaborate with
+industry partners to identify, analyse, and develop
+data-driven solutions tailored to specific business
+challenges
+Assessment Method
+Continuous Assessment: 100%
+
+
+## Shared Undergraduate Curriculum :: Specialization Elective Courses - Computer System and Network
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 240-244
+
+### Page 240
+te
+COURSE
+INFORMATION
+SPECIALIZATION
+ELECTIVE COURSES
+COMPUTER SYSTEM & NETWORK
+ey Ay A
+
+### Page 241
+wic2002
+NETWORK SECURITY
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Identify the importance of network security and the
+security applications and techniques used in a
+network.
+2. Design @ secure network topology based on the
+security elements.
+3. Apply the applications and techniques to solve a
+range of security problems in a network.
+Synopsis of Course Content
+This course is designed to provide student knowledge of
+network security, types of attack towards network,
+security services, and security mechanism. This course
+also will examine the security criteria by identity the best
+practices for the network security. The criteria will be
+looking into encryption techniques, remote access,
+intrusion detection and prevention, Virtual Private
+Network, firewall, honey pots, AAA, Infrastructure
+security, and physical security. Finally, the course will
+evaluate a plan and best proposal to design a secure
+network topology based on security policy and legal
+issues. This course also emphasis on practical
+exercises by introducing a range of security applications
+used in a network
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wic2004
+INTERNET TECHNOLOGY
+Credit: 3
+Course Pre-requisites): None
+Medium of Instruction: English
+Learning Outcomes
+Describe the Intemet and its evolution to the current
+technology.
+2. Identify the steps to evaluate and implement the
+technology, the model it was based on and the
+architecture
+3. Analyze the strength and weaknesses of each
+Internet technology implementation being discussed.
+4, Discuss security concer that must be considered
+when implementing the selected Internet technology.
+Synopsis of Course Content
+This course contains the introduction towards Internet
+and its evolution in introducing new technologies such as
+Internet of Everything, Cloud Computing and Software
+Defined Network. It explained the concept and steps of
+implementation of the technology discussed and how to
+implement it, It also discussed the strength and
+weaknesses of each Internet technology and the security
+issues related
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wic2005
+PROGRAMMABLE NETWORK
+Credit: 3
+Course Pre-requisite(s): WIA2008
+Medium of Instruction: English
+Learning Outcomes
+1. Describe the basic concept of network programming
+and Software Defined Networking (SDN)
+programming.
+2. Design and program client/server communication.
+3, Describe the deployment models of SDN and
+Network Functions Virtualization (NFV) using
+OpenFlow protocol
+Synopsis of Course Content
+This course introduces network programming and SDN
+programming. The contents include the introduction to
+the concept and programming of _ client/server
+communication; the fundamentals of SDN and_ its
+potential applications related to network function
+virtualization (NFV); Explores emerging applications of
+SDN; hands-on exercises of SDN programming
+environment with OpenFlow protocol and controller.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wic2006
+DIGITAL FORENSIC
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+Identify forensics and information security issues in
+digital domain,
+2. Differentiate various forensic techniques for digital
+media
+3. Apply appropriate digital forensic techniques for
+different digital media
+Synopsis of Course Content
+This course is designed to provide students with
+knowledge on various security issues and cybercrime.
+This course will also expose students to different stages
+in the digital forensic process. Students will also apply
+
+### Page 242
+Various digital forensic techniques in accordance with the
+identified media and applicable cybercrime laws.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 0%
+wic2007
+CYBER SECURITY
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the concept of cyberspace and cybersecurity
+including critical security controls for effective cyber
+defense.
+2. Determine suitable security controls for the defined
+security requirements.
+3. Investigate techniques used for auditing and
+monitoring the performance of cybersecurity
+controls.
+Synopsis of Course Content
+This course consists of the introduction on terms
+cyberspace, cybersecurity, related standards for best
+practices in cybersecurity, essential security
+requirements and security controls/functions for cyber
+defense, and security assessment techniques in cyber
+environment.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wic2008
+INTERNET OF THINGS.
+Credit: 3
+Course Pre-requisite(s): WIA1005
+Medium of Instruction: English
+Learning Outcomes
+1, Describe the basic concept of Internet-of-Things.
+2. Design loT application using existing technology.
+3. Apply loT knowledge of practical problem solving.
+Synopsis of Course Content
+The course provides an overview of Interet-of-Things
+technology concept and practical. It develops
+foundational skills using hands-on lab activities that
+stimulate the students in applying creative
+problem-solving and rapid prototyping in the
+interdisciplinary domain of electronics, networking,
+security, data analytics, and business. The
+student-centric approach translates into the student
+being able to produce ideas, design, prototype and
+present an loT solution for an identified business or
+society need.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wic3001
+MATHEMATICS IN NETWORKING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Identify the basic principles of probability and
+statistics behind computer networking,
+2. Discussing the techniques and applications of graph
+theory to solve computer networking problems.
+3. Evaluating the problems in queueing theory and
+network calculus related to computer networks.
+Synopsis of Course Content
+This course is designed to provide a practical aspect of
+basic statistics and mathematics on computer
+networking. It also an emphasis on problem-solving and
+analysis using the mathematical and statistical
+techniques in computer networking,
+‘Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+~~ wie3002
+CRYPTOGRAPHY
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+Explain the concept of cryptogrephy and techniques
+used clearly
+2. Distinguish different cryptography systems.
+3. Determine suitable technique or algorithm for
+implementation in a system accordingly.
+4, Investigate cryptographic algorithms in regards to
+their design and security analysis.
+Synopsis of Course Content
+This course consists of the introduction of cryptography,
+cryptographic techniques, computer-based Symmetric
+Ke
+‘Cryptographic Algoritis, computer-based Asymmetric
+Key Cryptographic Algorithms, Public Key Infrastructure
+(PKI), Internet Security Protocols (Implementation of
+Cryptography), user authentication _ mechanisms,
+practical implementations of cryptography and case
+studies.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+
+### Page 243
+wic3003
+EMBEDDED SYSTEM PROGRAMMING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the concept and architecture of an embedded
+system,
+Program an embedded system application.
+Apply interfaces technique between embedded
+applications system.
+3,
+‘Synopsis of Course Content
+This course covers the embedded system overview,
+embedded system memory management, embedded
+system interfaces and embedded system controller.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wic3004
+COMPUTER PENETRATION
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the concepts of computer penetration.
+2. Identify suitable techniques in computer penetration
+activity.
+3. Apply suitable computer penetration techniques in
+specific security scenario,
+‘Synopsis of Course Content
+This course introduces the concepts and techniques
+used to penetrate computers with a focus on ethical
+hacking. The contents of this course cover the basic
+steps of penetration testing such as reconnaissance,
+network scanning, exploitation of vulnerabilities, and
+maintaining access to penetrated systems.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+Wwic3005
+ENTERPRISE NETWORK DESIGN AND
+MANAGEMENT
+Credit: 3
+Course Pre-requisite(s): WIA1005
+Medium of Instruction: English
+Learning Outcomes
+4. Explain and design
+approach.
+2. Solve network management problem.
+3. Solve problems related to systematic network
+documentation, design and configuration,
+network using top-down
+Synopsis of Course Content
+This course consists of top-down network design model
+for large scale network which includes the requirements
+‘and constraints, large scale network topology design,
+models for addressing and naming for network devices.
+This course also covers switching and routing protocols,
+network security strategies, optimal network design,
+network management planning and strategy, ISO
+network management model, network management
+protocols: SNMP. RMON, NTP, network performance
+issues, troubleshooting mechanisms and network
+documentation and base lining,
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wic3006
+MOBILE COMPUTING
+Credit: 3
+Course Pre-requisite(s); None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the various wireless technologies and
+services.
+2. Discuss important issues and challenges in mobile
+computing,
+3. Build a mobile computing application that is
+according to the user requirements and operating
+environments.
+Synopsis of Course Content
+This course covers the introduction to wireless networks
+‘and mobile computing, which includes looking at
+examples of mobile computing applications, issues that
+cistinguishes wireless networks from fixed networks and
+‘examples of how the issues are addressed to support
+mobile computing.
+Assessment Methods
+Continuous Assessment: 50%
+
+### Page 244
+Final Examination: 50%
+wic3007
+PRINCIPLES OF DISTRIBUTED COMPUTING
+Credit: 3
+Course Pre-requisite(s):
+WIA1005 - Network Technology Foundation
+Medium of Instruction: English
+Learning Outcomes
+41. Determine the fundamental of distributed computing,
+2. Identify the issues, problems and the solutions in
+distributed computing.
+3, Implement distributed system.
+‘Synopsis of Course Content
+This course consists of top-down network design model
+for large scale network which includes the requirements
+and constraints, large scale network topology design,
+models for addressing and naming for network devices.
+This course also covers switching and routing protocols,
+network security strategies, optimal network design,
+network management planning and strategy, ISO
+network management model, network management
+protocols: SNMP, RMON, NTP, network performance
+issues, troubleshooting mechanisms and network
+documentation and base lining
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wic3008
+MICROPROCESSOR
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the basic concept and microprocessor
+architecture,
+2. Explain the processor interface and software design
+techniques.
+3. Executes the basic concept of microprocessor
+operation
+‘Synopsis of Course Content
+This course covers the introduction to microprocessor
+which includes Arithmetic processor, microprocessor
+development, instruction in microprocessor,
+microprocessor connection, microcontroller, advanced
+microprocessor, Input / Output in microprocessor and
+microprocessor development based on product.
+Assessment Methods
+Continuous Assessment: 50%
+wic3009
+PARALLEL PROGRAMMING
+Final Examination: 50%
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the fundamental of parallel computing,
+2. Apply fundamental concepts. of parallel
+programming
+3. Use GPU programming model and architecture, key
+algorithms, parallel programming pattems and
+‘optimization techniques.
+Synopsis of Course Content
+This course introduces the parallel programming model
+‘and hardware The course also includes how to optimize
+GPU programs and the future of GPU computing.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+
+
+## Shared Undergraduate Curriculum :: Specialization Elective Courses - Artificial Intelligence
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 245-249
+
+### Page 245
+al
+COURSE
+INFORMATION
+SPECIALIZATION
+ELECTIVE COURSES
+ARTIFICIAL INTELLIGENCE
+ny Ay AF
+
+### Page 246
+‘wic2008
+INTERNET OF THINGS.
+Credit: 3
+Course Pre-requisite(s): WIA1005
+Medium of Instruction: English
+Learning Outcomes
+1. Describe the basic concept of
+Intemet-of-Things.
+2. Design loT application using existing
+technology.
+3. Apply loT knowledge of practical problem
+solving
+Synopsis of Course Content
+The course provides an overview of
+Interet-of-Things technology concept and
+practical. It develops foundational skills using
+hands-on lab activities that stimulate the students in
+applying creative problem-solving and rapid
+prototyping in the interdisciplinary domain of
+electronics, networking, security, data analytics,
+and business. The student-centric approach
+translates into the student being able to produce
+ideas, design, prototype and present an loT
+solution for an identified business or society need,
+Assessment Methods
+Continuous Assessment: 50%.
+Final Examination: 60%
+wib2001
+KNOWLEDGE REPRESENTATION AND
+REASONING
+Credit: 3
+Medium of Instruction: English
+Laarring Oukcomes
+Describe types of knowledge and their
+engineering processes.
+2. Differentiate the various knowledge
+representation and knowledge reasoning
+methods.
+3. Use the various knowledge representation and
+knowledge reasoning methods to solve
+problems.
+Synopsis of Course Content
+This course describes types of knowledge and their
+engineering processes as used in expert system
+development. It differentiates the various
+knowledge representations methods such as logic,
+rule-based, frame-based, semantic network, script,
+conceptual dependency, and ontology. It also
+explains the various knowledge reasoning methods
+such as the deductive, inductive, monotonic, and
+non-monotonic reasoning. Students will use the
+various knowledge representation and knowledge
+reasoning methods to solve problems.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wib2002
+COMPUTING MATHEMATICS II
+Credit: 3
+Course Pre-requisite(s): None
+Medium of instruction: English
+Learning Outcomes
+Apply various formulae for operations on
+differentiation and integration aswell as
+mathematical transformation (Calculus).
+2. Apply the principles of algebraic matrix in
+problem solving (Linear Algebra)
+3. Apply statistical methods in problem solving
+(Statistics).
+Synopsis of Course Content
+This course covers important mathematics t
+which can be applied to the artificial intelligence
+field. The topics include calculus (differentiation
+and integration), functions and graphs, matrix
+algebra (Eigen value, Eigen vector, dependency,
+singularity), statistical methods (sampling, principal
+‘component analysis) and transformations (Fourier,
+Laplace etc.)
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+‘wiD2003
+COGNITIVE SCIENCE
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Identify various cognitive concepts and
+processes,
+2. Describe memory functions related to learning
+activities,
+3. Apply cognitive theories in everyday problem
+solving.
+Synopsis of Course Content
+This course covers the fundamentals on cognitive
+science. It covers topics on mind and machine,
+perception (object recognition), attention &
+consciousness, memory (short term memory,
+working memory and long term memory), forgetting,
+
+### Page 247
+mental representation and visual perception,
+category, language, intelligence and creativity
+emotion and expression, problem solving, reasoning
+and decision making
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WID3001
+FUNCTIONAL AND LOGIC PROGRAMMING
+Credit: 3
+Medium of Instruction: English
+Learning Outcomes
+1 Describe basic principles and features of
+functional and logic programming.
+2. Explain concepts and methods of functional and
+logic programming
+3. Apply functional and logic programming
+knowledge.
+Synopsis of Course Content
+This course introduces Artificial Intelligence (Al)
+programming languages, which covers functional
+and logic styles of programming. It describes the
+functional programming that uses functions as its
+basis and includes topics such as types and
+classes, lists, recursions, and higher-order
+functions. The logic programming is based on
+formal logic and includes topics such as clauses
+‘and predicates, unification, operators. and
+arithmetic, cuts and negation.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wip3002
+NATURAL LANGUAGE PROCESSING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Identify the various levels of natural language
+processing.
+2. Explain the approaches and applications of
+natural language processing
+3, Apply natural language processing techniques
+to solve problems.
+Synopsis of Course Content
+The course introduces the theory and methods of
+Natural Language Processing (NLP). It covers @
+broad range of topics in NLP including basic text
+processing, minimum edit distance, syntactic
+analysis, and semantic analysis. In addition, it also
+discusses some NLP applications such as machine
+translation and sentiment analysis.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+‘WID3007
+FUZZY LOGIC
+Credit: 3
+Course Pre-requisite(s): WIX1001
+Medium of Instruction: English
+Learning Outcomes
+Understand the concept and techniques of
+fuzzy set theory and fuzzy logic
+istinguish fuzzy rules and fuzzy relations from
+their crisp counterparts.
+3. Implement fuzzy inference systems and fuzzy
+clustering techniques in problem solving
+‘Synopsis of Course Content
+This course begins with definition, concept, and
+examples of fuzzy logic. It covers fuzzy sets, rules,
+operations, relations, and membership functions. It
+also discuss fuzzy logics, _fuzzifcation,
+defuzzification, fuzzy systems, and future
+applications.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wiD3010
+AUTONOMOUS ROBOTS
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+Describe various robot components such as
+sensors, actuators and computational nodes.
+2. Discuss conceptual and technical challenges in
+autonomous robots.
+3. Apply methods for decision making in
+autonomous robots.
+Synopsis of Course Contents
+This course introduces the basic concept of
+autonomous system by making robots that can
+observe, reason and act. The syllabus includes
+leaming how robots interpret noisy sensor inputs,
+control its actions, recover from failures, react
+versus feason about @ situation, solve
+sub-problems, solve long-term goals and coexist in
+the world. In this course, students will study
+
+### Page 248
+methodologies to achieve autonomous robot
+system through practical and ground up approach
+of programming your own
+Assessment Methods
+Continuous Assessment: 70%
+Final Examination: 30%
+‘wiD3011
+DEEP LEARNING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Describe components of architecture of artificial
+neural network and convolutional neural
+network.
+2. Compare categories of supervised and
+unsupervised deep network.
+3. Apply suitable leaming rule for a problem.
+Synopsis of Course Content
+‘The purpose of this course is to give the students a
+clear introduction, an intuitive understanding and a
+smooth Python’ implementation of the most
+successful deep learning techniques. The teaching
+approach provides a good balance of theory and
+ctice. Theory of deep neural networks relies on
+simple linear operations and basic gradient descent
+optimization. Practical exercises of deep learning
+applications will focus on PyTorch. Each lecture
+presents the fundamental concepts and translates
+them into PyTorch implementations.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wip3012
+EVOLUTIONARY COMPUTATION
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain evolutionary computation techniques
+and methodologies set in the context of modern
+heuristic methods.
+2. Apply various evolutionary computation
+methods and algorithms for particular classes of
+problems.
+3. Develop evolutionary algorithms for real-world
+applications.
+Synopsis of Course Content
+The course aims to introduce students to a wide
+range of Evolutionary Computation terminology,
+techniques, and processes. The concepts taught in
+these lectures will be practiced and reinforced by
+Participation in projects.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WID3013
+COMPUTER VISION AND PATTERN
+RECOGNITION
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain basic concepts, terminology, theories,
+models and methods in the field of computer
+vision and pattern recognition
+2. Describe known principles of human visual
+system.
+3. Suggest a design of a computer vision or
+pattern recognition system for a specific
+problem,
+‘Synopsis of Course Content
+Ever wonder how robots can navigate space and
+perform duties, how search engines can index
+billions of images and videos, how algorithms can
+diagnose medical images for diseases, how
+self-driving cars can see and drive safely or how
+Instagram creates fiters or snapchat creates
+masks? In this course, we will explore all of these
+technologies and leam to prototype them. Lying in
+the heart of these modern Al applications are
+computer vision and pattem recognition
+technologies that can perceive, understand and
+reconstruct the complex visual world. Computer
+Vision and Pattern Recognition is one of the fastest
+growing and most exciting Al disciplines in today’s
+academia and industry. This course is designed to
+open the doors for students who are interested in
+leaming about the fundamental principles and
+important applications of computer vision and
+pattern recognition. We will expose students to a
+number of real-world applications that are
+important to our daily lives. More importantly, we
+will guide students through a series of well
+designed projects such that they will get to
+implement a few interesting and cutting-edge
+computer vision and pattern recognition algorithms.
+Assessment Method
+Continuous Assessment: 50%
+Final Examination: 0%
+
+### Page 249
+wiD3014
+PRATICAL ARTIFICIAL INTELLIGENCE
+wic3004
+VIRTUAL REALITY
+Credit: 3
+Course Pre-requisite(s); None
+Medium of Instruction: English
+Learning Outcomes
+Identify solution approach that is suitable for the
+stated problem
+2. Conduct suitable requirement gathering, system
+analysis and design techniques.
+3. Present the project solution.
+Synopsis of Course Content
+This course covers the practical activities including
+system analysis and design, —_system
+implementation, testing and evaluating the
+developed system and project presentation
+Assessment Methods
+Continuous Assessment: 100%
+WID3015
+NUMERICAL ANALYSIS
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1, Solve equations using numerical methods
+2. Apply numerical methods in order to solve
+differentiation/integration problems.
+Synopsis of Course Content
+This course covers numerical analysis end the
+computer implementation of numerical problems.
+Topics include, interpolation & function
+approximation, system of linear equations solving
+algebraic equations, numerical differentiation and
+integration and numerical solution of ordinary
+differential equations.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+Credit: 3
+Course Pre-requisite(s): Tiada
+Medium of Instruction: English
+Learning Outcomes
+Explain the technology that support virtual
+reality applications and human perceptions
+involved in designing virtual reality environment
+2. Discuss other technologies including
+visualization and augmented reality
+3. Develop a virtual reality environment using
+suitable tools and programming language
+‘Synopsis of Course Content
+This course begins with some introduction to virtual
+reality technology and its applications, followed by
+detail explanation regarding input and output
+devices that are being used in virtual reality
+application. Students will also learn about human
+sensory systems (visual, audio and tactile) and
+their relations to the development of virtual reality
+devices, as well as the possible effects these
+devices have on human health, Then students will
+be taught about how to model a virtual reality world
+and manipulate its objects using virtual reality
+development tools and programming languages
+The course ends by providing students with
+fundamental knowledge regarding data
+visualisation and augmented reality, a research
+area that is closely related to virtual reality
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+
+
+## Shared Undergraduate Curriculum :: Specialization Elective Courses - Information Systems
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 250-254
+
+### Page 250
+COURSE
+INFORMATION
+SPECIALIZATION
+ELECTIVE COURSES
+INFORMATION SYSTEMS
+ny Ay A
+
+### Page 251
+wic2008
+INTERNET OF THINGS
+Credit: 3
+Course Pre-requisite(s): WiA1005
+Medium of Instruction: English
+Learning Outcomes
+1. Describe the basic concept of Intemet-of- Things.
+2. Design loT application using existing technology.
+3. Apply loT knowledge of practical problem solving
+‘Synopsis of Course Content
+The course provides an overview of Interet-of-Things.
+technology concept and practical. It develops
+foundational skills using hands-on lab activities that
+stimulate the students in applying creative
+problem-solving and rapid prototyping in the
+interdisciplinary domain of electronics, networking,
+security, data analytics, and business. The
+student-centric approach translates into the student
+being able to produce ideas, design, prototype and
+present an loT solution for an identified business or
+society need.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 0%
+WIE2001
+TRENDS IN INFORMATION SYSTEMS
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Describe emerging computer __ technologies,
+industry-specific information systems, and current
+trends in information systems.
+2. Discuss critical issues related to managing and
+administering the discussed information systems or
+technologies.
+3. Apply tools or model to relevant cases or data,
+Synopsis of Course Content
+This course explores selected topics of specialized
+content (not usually covered by the other courses) as
+determined by the department and the lecturer with
+emphasis on current Information System trends.
+Topics under this course heading vary from year to year
+according to the developments in computer technology
+and information systems.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wie2002
+OPEN-SOURCE PROGRAMMING: APPLICATION AND
+TECHNOLOGY
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain basic characteristics and concepts of open
+source applications and technology.
+2. Use open source programming language to populate,
+update and retrieve database/ dataset,
+3. Develop open source solution to resolve a business
+problem
+‘Synopsis of Course Content
+This course will enable students to learn the basic
+characteristics and concepts of open source applications
+and technology. Student will be able to write applications
+using open source programming in order to populate,
+retrieve and update database. They will also develop an
+open source solution to resolve a business problem.
+‘Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+Credit: 3
+Course Pre-requisite(s): None
+Medium of instruction: English
+Learning Outcomes
+Explain the key concepts relevant to data science
+including all processes in the data science life cycle
+and data science applications in real-world.
+2. Determine suitable tools, technologies and the core
+algorithms underlying an end-to-end data science
+workflow, including the experimental design, data
+collection, mining, analysis, and presentation of
+information derived from datasets
+3. Interpret the ethical implications on the use of data
+and technologies in data science process.
+‘Synopsis of Course Content
+The course is designed to help the student learn
+fundamental concepts of data science. It covers the
+What, when, who, where, why and how (SW 1H) of data
+science in the era of big data. Also encompass, the life
+cycle of data science from data preparation, data
+processing, data cleansing and integration, to data
+analysis and visualization of data in data-driven decision
+making. The role of data scientist, the knowledge and
+skills required is also presented. Machine learning
+algorithms and statistical models are included. Diverse
+technologies, programming languages as well as tools in
+data science are discussed.
+Assessment Methods
+Continuous Assessment: 60%
+___@
+
+### Page 252
+Final Examination: 40%
+WiE2005
+INFORMATION RETRIEVAL AND WEB SEARCH.
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Define how the Web is organized and its
+fundamental properties.
+2. Explain how search engines collect Web content,
+index it, and present the most relevant results for a
+given query.
+3. Solve problems related to effective information
+retrieval or evaluation of search engine
+performances.
+‘Synopsis of Course Content
+The objective of this course is to examine the main
+computer science principles that lie behind search
+engines. For this purpose, focus will be given to the
+Information Retrieval (IR), which is described as "the
+science of searching for information in documents,
+searching for documents themselves, searching for
+metadata which describe documents, or searching
+within databases, whether relational stand-alone or
+hypertextually-networked such as the World Wide Web"
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WiE3001
+ADVANCED DATABASE
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Administer the database.
+2. Employ basic monitoring procedures.
+3. Apply distributed database and big data.
+‘Synopsis of Course Content
+Enable students to play the role of a database
+administrator and perform tasks such as creating
+database instances, managing storage structures,
+schema objects, data concurrency, undo data,
+administrating users security and configuring database.
+This course will enable students to understand how
+distributed database and big data management are
+implemented,
+‘Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WiE3002
+ELECTRONIC COMMERCE
+Credit: 3
+Course Pre-requisite(s): None
+Medium of instruction: English
+Learning Outcomes
+1. Explain technologies, standards and business
+processes involved in implementing electronic
+commerce.
+2. Apply advance modes on usage of information
+technology in business activities to boost new
+opportunities developed from the usage of Internet
+among its users.
+3. Build simple e-commerce applications for specific
+areas of business that have _ potential
+commercialization values.
+Synopsis of Course Content
+This course consists of the following components:
+{a) Introduction of E-Commerce (b) E-Commerce
+Infrastructure: The Internet, Web and Mobile Platform; (c)
+Building an E-commerce Presence: Web Sites, Mobile
+Sites and Apps; (d) E-Commerce Security and Payment
+Systems; (e) E-Commerce Business Models and
+Concepts; (f) E-Commerce Marketing and Advertising
+(g) Social, Mobile and Local Marketing: (h) Ethics, Law
+and E-Commerce; (i) Online Content and Media ())
+Social Networks, Auctions and Portals, and (k)
+E-Commerce Retailing and Services.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WIE3003
+INFORMATION SYSTEM CONTROL AND SECURITY
+Credit; 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Identify control and security involve in an information
+systems from the physical/environmental perspective,
+application perspective and operational perspective.
+2. Describe types of current security control for the
+information system organisation, including the
+methodology, procedure and implementation design.
+3. Solve security problems in information system using
+workflow, procedure and control being studied
+Synopsis of Course Contents
+There are ten elements of the syllabus of the course are;
+(2) Information Security and Risk Management; (b)
+Threats and attacks in information systems (c) Access
+Control System and Methodology; (d) Cryptography; (e)
+Physical/Environmental Security; (f) Enterprise security
+system architecture and design; (g) Business Continuity
+and Disaster Recovery Planning; (h) Telecommunication,
+Networks and Internet Security; (i) Application Security;
+(j) Operation Security.
+
+### Page 253
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WIE3005
+KNOWLEDGE MANAGEMENT AND ENGINEERING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1, Describe the concepts and technological approaches
+of Knowledge Management and Engineering (KME).
+2. Use of various tools and methods for KME.
+3. Use working knowledge and skills to plan, assess
+and develop knowledge management system.
+‘Synopsis of Course Content
+Modules for this course include (a) An introduction to the
+concepts Knowledge Management and Engineering; (b)
+Knowledge Characteristics: knowledge and its
+differences from data and information; (c) Techniques in
+KME: capturing, encoding and measuring of knowledge
+(d) Technological approach towards knowledge; (e)
+Concepts of Ontology, Taxonomy and related knowledge
+construction tools (f) Developing knowledge
+management system, evaluating the knowledge needs
+of an organisation; (g) Case study on KME in
+organization.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WIE3006
+INFORMATION SYSTEM AUDITING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Understand the processes, principle and method of
+information system auditing.
+2. Identify effective auditing processes and tools for
+information systems.
+3. Use the works, procedures and control leamed to
+solve current problems faced by organisations for
+effective auditing purpose.
+‘Synopsis of Course Content
+The topics that make up the course are: (a) Auditing
+process; (b) Managing planning and organization of
+information systems; (c) Technical infrastructure and
+operational work procedure; (d) Control on information
+assets; (2) Disaster recovery and business
+sustainability; (f) System development of Business
+applications, findings, implementation and operations:
+(9) Evaluation of business process and risk
+management.
+Assessment Method
+Continuous Assessment: 50%
+Final Examination: 50%
+WIE3007
+DATA MINING AND WAREHOUSING
+Credit: 3
+Course Pre-requisite(s): None
+‘Medium of Instruction: English
+Learning Outcomes
+1. Define the term Data Mining and Data Warehouse.
+2. Draw a schema diagram for the data warehouse
+using Star schema.
+3. Create a decision tree (DT) model using the 1D3
+algorithm to find frequent itemsets using Aprior
+‘Synopsis of Course Content
+The course consists of the following components: (a)
+Introduction to Data Werehouse and Data Mining; (b)
+Data Warehouses; (c) Pre-mining; (d) Classification; (e)
+Association Rules; (f) Clustering Algorithms.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WIE3010
+DATA VISUALIZATION
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+Explain concepts and techniques relevant to data
+Visualization, ie; data aspects, modeling concepts,
+and visualization techniques.
+2. Apply suitable visualization techniques to
+appropriate datasets.
+3. Use appropriate tools. to analyze, and
+presentivisualize data
+‘Synopsis of Course Content
+This course begins by introducing the concepts of data
+visualization vs infographics. It provides students with
+the knowledge of where data can be found (data
+sources), how data can be acquired and how data can
+be analyzed and presented. It explains topics such as
+modeling concepts, data aspects, and visualization
+techniques. Techniques for visualizing multivariate,
+temporal, text-based, geospatial, and other types of data
+are taught. Students will be exposed to a few tools: to
+capture/import data, to analyze data and to visualize
+data.
+‘Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+
+### Page 254
+WIE3012
+BUSINESS ANALYTICS AND INTELLIGENCE
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the concept of BI and implementation of Data
+warehouse.
+2. Integrate data from different sources.
+3. Use suitable methods and techniques to analyse
+OLAP data to solve business problems
+‘Synopsis of Course Content
+This course discusses Online analytical processing
+(OLAP), Data warehouses end data Dimensional
+modelling, Extract Transform Load (ETL) design, and
+statistical and mining approaches to improve business. It
+also covers report design, development and emerging
+trends in business intelligence.
+Assessment Methods
+Continuous Assessment: 70%
+Final Examination: 30
+WIF2003
+WEB PROGRAMMING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Use different programming languages, techniques,
+platforms and tools for web development.
+2. Use frameworks and database to develop web
+applications.
+3. Apply different techniques to improve the quality of
+web applications.
+Synopsis of Course Content
+This course covers the techniques, frameworks,
+platforms and tools for Web development. Theoretical
+aspects include the concepts of Web development,
+stack technologies, client-server architecture, and
+quality attributes of Web-based systems. Technical
+aspects include topics on design and development of
+web database applications using different protocols,
+programming languages, techniques, frameworks,
+platforms and tools, taking relevant quality issues into
+consideration.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+
+
+## Shared Undergraduate Curriculum :: Specialization Elective Courses - Software Engineering
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 255-259
+
+### Page 255
+COURSE
+INFORMATION
+SPECIALIZATION
+ELECTIVE COURSES
+SOFTWARE ENGINEERING
+i Ay
+
+### Page 256
+wiF2002
+SOFTWARE REQUIREMENTS ENGINEERING
+Credit 23
+Course Prerequisite(s) : None
+Medium of Instruction: English
+Learning Outcomes
+To describe issues in software requirements
+engineering.
+2. To provide requirement artefacts based on
+established standards.
+3. To apply appropriate techniques and methods
+to elicit and analyse software requirements.
+4, To use proper models and tools for managing
+and verifying requirements.
+Synopsis of Course Content
+This course covers the fundamentals of
+requirements engineering: important requirements
+artefacts are covered and discussed. Core
+activities of requirement engineering which include
+elicitation, specification, documentation,
+negotiation, validation, and management ere
+explained.
+Assessment Methods
+Continuous Assessment : 50%
+Final Examination 50%
+WwiF2003
+WEB PROGRAMMING
+Credit S
+Course Prerequisite(s) : None
+Medium of Instruction —: English
+Learning Outcomes
+1. Use diferent programming languages,
+techniques, platforms, and tools for web
+development.
+2. Use frameworks and database to develop web
+applications.
+3. Apply different techniques to improve the
+quality of web applications.
+Synopsis of Course Content
+This course covers the techniques, frameworks,
+platforms, and tools for Web development.
+Theoretical aspects include the concepts of Web
+development, stack technologies, client-server
+architecture, and quality attributes of Web-based
+systems. Technical aspects include topics on
+design and development of web database
+applications using —_ different -—_ protocols,
+programming languages, techniques, frameworks,
+platforms, and tools, taking relevant quality issues
+into consideration.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination 50%
+WiF3001
+‘SOFTWARE TESTING
+Credit 23
+Course Prerequisites): None
+Medium of Instruction — : English
+Learning Outcomes
+Explain between various levels of testing, test
+types, and test approaches in test based
+software development,
+2. Analyse the test design techniques of static
+approach in software development phases
+3. Apply the test design techniques of dynamic
+approach within test process
+Synopsis of Course Content
+This course is designed to provide with in-depth
+knowledge on software testing and its test
+process. The course covers the basic principles of
+software testing and test activities that include the
+test plan, test design, monitoring, implementation,
+and test closure. The students will also leam
+various categories of test design techniques and
+methods used in both black box and white box
+testing of static and dynamic approaches. At the
+‘end of this course, students should be able to
+recognize various types and levels of testing as
+well as categorizing and applying software testing
+process and techniques.
+Assessment Methods
+Continuous Assessment 50%
+Final Examination 50%
+wiF3002
+‘SOFTWARE PROCESS AND QUALITY
+Credit 13
+Course Prerequisite(s) _: None
+Medium of Instruction: English
+Learning Outcomes
+1. Describe the fundamental concepts of software
+quality, software process, _ measurement
+rogram, and sofware process improvement,
+2. Apply the principles of measurement and
+improvement program as part of software
+quality assurance activity to produce high
+quality arifacts in software development
+process.
+3. Evaluate various software process
+improvement models and quality management
+
+### Page 257
+standard.
+Synopsis of Course Content
+This course covers software quality, software
+process, and sofware process improvement. It
+introduces the softwere quality assurance and the
+importance of process quality. Various existing
+software development methodologies are also
+being studied. It is followed by measurement
+program as part of software quality assurance
+activity to produce quality artifacts. The later part
+discusses software process improvement. Various
+models that support software process
+improvement are presented, and these include the
+CMMI, ISO $000, SPICE, PSP and TSP.
+Assessment Methods
+Continuous Assessment : 50%
+Final Examination 50%
+WiF3004
+SOFTWARE ARCHITECTURE AND DESIGN
+PARADIGMS:
+Credit ne
+Course Prerequisite(s) : WiA2002
+Medium of Instruction: English
+Learning Outcomes
+Differentiate between function-oriented, object-
+oriented, and data-structure centered design
+methods.
+2. Apply the design principles in producing
+software architecture desion.
+3. Analyze software architecture.
+‘Synopsis of Course Contents
+This course covers software design issues and
+design principles; the different types of design
+methods such as function-oriented design,
+object-oriented design (emphasizing on
+deployment diagram), data-structure centered
+design; architecture design; architectural
+structures and views; quality attributes; tactics to
+achieve quality attributes; architectural
+styles/patterns (such as client-server, peer-to-peer,
+layered, and so on); introduction to design
+patterns; domain specific architectures; and tools.
+Assessment Methods
+Continuous Assessment : 50%
+Final Examination 50%
+WiF3005
+SOFTWARE MAINTENANCE AND EVOLUTION
+Creait :3
+Course Prerequisite(s) _: None
+Medium of Instruction: English
+Learning Outcomes
+The fundamentals of software maintenance,
+maintenance processes, and activities.
+2. Apply suitable techniques and tools for
+performing software maintenance activities.
+3. Assess various strategies for evolving a legacy
+software system
+Synopsis of Course Content
+This course mainly covers software maintenance
+fundamentals, key issues in maintenance,
+maintenance process, techniques for
+maintenance, and evolution in maintenance
+activities. Topics include definitions, terminology
+and categories of maintenance (Corrective
+Maintenance, Perfective Maintenance, Adaptive
+Maintenance, Preventive Maintenance); evolution
+of software; technical and management issues in
+maintenance (such as technical issues related to
+testing, impact analysis, and maintainability;
+management issues such as staffing, process,
+organizational aspects, and outsourcing and
+offshoring); maintenance cost estimation and
+measurement; maintenance processes and
+activities (such es maintenance planning activities,
+software configuration management (configuration
+item, processes, and activities in configuration
+management, patches), activities for software
+quality); techniques for maintenance such as
+program comprehension, reengineering, reverse
+engineering, migration, and retirement; evolution
+of legacy systems; usage of tools related to
+maintenance (such as for_—_program
+comprehension, reverse engineering,
+configuration management).
+Assessment Methods
+Continuous Assessment 50%
+Final Examination 50%
+WIF3006
+COMPONENT-BASED SOFTWARE ENGINEERING
+Credit :3
+Course Prerequisite(s) : WiA2002
+Medium of Instruction: English
+Learning Outcomes
+1. Explain fundamental concepts, principles, and
+techniques in software reuse specifically on
+development for reuse, development by reuse,
+and component-level design.
+
+### Page 258
+2. Analyze changes to the existing application
+using component-based approach.
+3. Develop component-based application using
+various component frameworks and
+programming APIs.
+Synopsis of Course Content
+This course covers the fundamental concepts and
+principles of software reuse, componentlevel
+development, developmentidesign for reuse,
+developmentidesign by reuse, and design
+pattems, It includes the definition and explanation
+of the nature of components, components
+interfaces, Interfaces as contracts, benefits of
+components, component design, and assembly. It
+introduces the architecture of component-based
+systems, component-based software engineering
+frameworks such as SCA, Spring, OSGi, EJB, and
+also covers component-based computing, API
+programming, class browsers, and related tools,
+as well as debugging in the API environment.
+Assessment Methods
+Continuous Assessment : 50%
+Final Examination 1 50%
+WIF3008
+REAL TIME SYSTEMS
+Credit
+Course Prerequisite(s) _: None
+Medium of Instruction: English
+Learning Outcomes
+1. Define the principles of real time systems and
+compare real time system architectures.
+2. Implement algorithms and protocols for
+scheduling, analysis, and verification for
+real-time systems
+3. Solve problems related to real-time issues in
+communication networks, specifically, features
+and capabilities required to support realtime
+applications.
+Synopsis of Course Content
+This course introduces real time systems. The
+ferences between soft and hard real time
+systems are explained. Issues related to system
+decomposition and scheduling techniques are
+discussed. These include Timed Petri Net,
+clock-criven scheduling, as well as priority-criven
+scheduling of periodic, aperiodic, and sporadic
+tasks. Apart from that, the course also covers
+issues such 2s multiprocessor scheduling and
+resource access control, fault tolerance, and real
+time communication.
+Assessment Methods
+Continuous Assessment : 50%
+Final Examination 50%
+WIF3009
+PYTHON FOR SCIENTIFIC COMPUTING
+Credit 3
+Course Prerequisite(s) _: None
+Medium of Instruction: English
+Learning Outcomes
+1, Explain scientific computation using Python in
+problem solving
+2. Use Python to create a variety of scripts and
+applications for the Web and systems
+development.
+3. Apply key packages of Python to solve
+complex and nontrivial problems in a software
+project
+Synopsis of Course Content
+This course introduces the landscape of scientific
+computing and core Python language using simple
+examples drawn from mathematics and physics. It
+discusses some of the ecosystem of scientific
+libraries, in particular, the SciPy ecosystem which
+includes general and specialised tools for data
+management and computation, productive
+experimentation and high-performance computing.
+These tools include Pandas, SymPy, |Python,
+IPyParallel, and Matplotiib. These state-of-the-art
+tools and key packages allow students to solve
+complex and nontrivial problems rapidly, efficiently
+and correctly using numerical, symbolical, and
+scientific computing approach.
+Assessment Methods
+Continuous Assessment 60%
+Final Examination 40%
+WiF3010
+PROGRAMMING LANGUAGE PARADIGM
+Credit 23
+Course Prerequisites): None
+Medium of Instruction: English
+Learning Outcomes
+1. To describe characteristics and privilege of
+various programming language paradigms.
+2. To use formal notation and suitable tools for
+defining programming language syntax.
+3. To evaluate programming language design
+issues.
+Synopsis of Course Content
+This course covers the fundamentals concepts and
+paradigm of programming languages, discusses
+the various programming language constructs and
+their unique characteristics as well as their
+implementation techniques. It also analyzes the
+
+### Page 259
+formal methods of describing the syntax and
+semantics of programming languages
+‘Assessment Methods
+Continuous Assessment: 50%
+Final Examination 50%
+WIFsO11
+CONCURRENT AND PARALLEL PROGRAMMING
+Credit
+Course Prerequisite(s) _: WIX1002 & WIA2004
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the concepts and issues of concurrent
+and parallel processing
+2. Optimize execution of sequential code with
+concurrent and parallel processing
+3. Build algorithms to solve concurrent and
+parallel processing problems,
+Synopsis of Course Content
+Concurrent and parallel programming plays a vital
+ole in processing a complex problem in a
+concurrent or parallel approach to improve overall
+performance of problem solving. This course
+explains the reasons and challenges in designing
+and implementing a concurrent or parallel program.
+Students will leam different models and
+programming constructs for concurrency and
+parallelism, This course also discusses evaluation
+of worthiness to make @ sequential program
+concurrent or parallel
+Assessment Methods
+Continuous Assessment : 50%
+Final Examination 50%
+wic2008.
+INTERNET OF THINGS
+Credit
+Course Prerequisite(s) : WIA1005
+Medium of Instruction:
+nglish
+Learning Outcomes
+1. Describe the basic concept of
+Intemet-of-Things
+2. Design loT application using existing
+technology.
+3. Apply loT knowledge of practical problem
+solving,
+Synopsis of Course Content
+The course provides an overview of
+Internet-of-Things technology concept and
+practical. It develops foundational skills using
+hands-on lab activities that stimulate the students
+in applying creative problem-solving and rapid
+prototyping in the interdisciplinary domain of
+electronics, networking, security, data analytics,
+and business. The student-centric approach
+translates into the student being able to produce
+ideas, design, prototype, and present an loT
+solution for an identified business or society need.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination 50%
+‘WIG3005
+GAME DEVELOPMENT
+Credit 33
+Course Prerequisite(s) _: None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the basic principles of computer games,
+game genre, game development life cycle, and
+design consideration
+2. Develop a computer game taking into
+consideration selected game genre.
+3. Explain the collision detection in game
+programming.
+Synopsis of Course Content
+This course will give an introduction to computer
+game development starting from concept
+development to implementation of a playable game
+prototype. Both the aesthetic and technical aspects
+of game development will be covered. The
+aesthetic component of the course will focus on
+story and character development, game
+mechanics, game play, and interface design and
+content creation for games, The technical
+of the course will focus on
+g tools and concepts for games,
+including data structures and algorithms, computer
+graphics, human-computer interaction, collision
+detection, and Al. Common topics include project
+management, prototype development, and play
+testing. Students will work in groups and go
+through the complete pipeline starting from a basic
+game idea all the way through developing a
+playable prototype.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination 50%
+
+
+## Shared Undergraduate Curriculum :: Specialization Elective Courses - Multimedia Computing
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 260-264
+
+### Page 260
+te
+\ \\
+COURSE
+INFORMATION
+SPECIALIZATION
+ELECTIVE COURSES
+MULTIMEDIA COMPUTING
+i Ay
+
+### Page 261
+wi2001
+DIGITAL IMAGE PROCESSING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Identify techniques of digital image processing
+specifically
+2. Explain and differentiate the usage of
+techniques in digital image processing.
+3. Apply several digital image processing
+techniques.
+ferent
+Synopsis of Course Content
+This course covers topics in digital image
+processing including image representation, image
+enhancement, image restoration, line and edge
+detection, image segmentation and image
+representation and description.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wiG2002
+COMPUTER GRAPHICS
+Credit: 3
+Course Pre-requisite(
+Medium of Instruction: English
+Learning Outcomes
+1. Understand the basic principles of
+implementing 2D and 3D computer graphics
+primitives.
+2, Explain the key algorithms for modelling and
+rendering graphical objects.
+3. Create interactive graphics program using a
+computer graphics API.
+Synopsis of Course Content
+The course will cover the main topics in computer
+gtaphics such as: graphics system, camera model,
+graphics primitives, graphics coordinate system,
+2D and 3D transformations, 2D and 3D viewing
+transformations, lighting, shadowing and texture
+mapping. Students will be using an open-source
+graphics API to create both 2D and 3D graphic
+objects.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wig2004
+‘AUDIO SYNTHESIS
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain audio synthesis techniques and audio
+control
+2. Synthesize a digital audio file in aif, wav and
+midi format.
+3. Discuss about the characteristics of a speech
+synthesis and speech recognition systems.
+‘Synopsis of Course Content
+This course starts with an introduction to the
+characteristics of sound in terms of physical and
+acoustical sounds, followed by the subsequent
+topics: properties of a sound wave, its relations to
+human perception of sound, sounds sampling and
+sound processing tools. Next, students will be
+taught about CSound programming emphasizing
+on the syntax of both the orchestra and score files,
+and how to program these files according to certain
+synthesis techniques in order to produce an audio
+file. For this purpose, students will be taught
+common synthesis techniques such as additive,
+subtractive, FM (Frequency Modulation) and AM
+(Amplitude Modulation). The course ends with an
+overview and hands on session of Audacity so
+students are able to relate what they have learned
+and how it is being used in developing software to
+‘manipulate or edit audio.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wiG2005
+INTERACTIVE DESIGN
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Identify task analysis for interactive design.
+2. Explain the design of _ interactive
+computer-based applications.
+3. Develop an interactive computer-based
+application.
+4. Evaluate an interactive computer-based
+application.
+‘Synopsis of Course Content
+
+### Page 262
+This course covers the main topics in interactive
+design such as the following: interaction concept
+and design; user roles in interactive design; design
+for combining information and communication
+effective aspects of interface and interactivity; data
+collecting, analyzing, and presentation; interactive
+design process; and interactive design evaluation
+process.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wi3001
+MATHEMATICS FOR MULTIMEDIA
+Credit: 3
+Course Pre-requisite(s); None
+Medium of Instructio
+: English
+Learning Outcomes
+1. Identify mathematical theories involved in
+multimedia signal processing.
+2. Elaborate mathematical techniques used in
+multimedia application.
+3. Apply mathematics theories in processing
+multimedia objects.
+Synopsis of Course Content
+This course covers topics such as numbers and
+arithmetic: space and linearity; time and
+frequency;sampling and estimation; scaling and
+resolution; redundancy and _information;error
+detection and correction,
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wic3002
+RENDERING AND ANIMATION
+Credit: 3
+Course Presrequisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the techniques used in modeling,
+texturing, animating and rendering process.
+2. Differentiate algorithms involved in generating
+3D objects.
+3. Discuss the importance of 30 computer
+animation and relate it to their daily
+Synopsis of Course Content
+At the beginning of this course, students will be
+exposed to the development, technology and
+computer animation applications. Next, students
+will be taught about the main phases in the
+development of computer animation which include
+aspects such as modeling, animation, texturing
+lighting, knowledge pertaining to. the job
+opportunities and future of computer animation and
+rendering.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WiG3003
+MULTIMEDIA PROGRAMMING
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the concept and syntax of Java
+programming used to develop a muttimedia
+application.
+2. Apply the multimedia elements in programming
+various mobile applications (Android & iOS).
+3. Develop multimedia application using Java
+programming language.
+Synopsis of Course Contents
+This course covers the following topics:
+object-oriented programming concept; the structure
+and concept in Java object-oriented programming
+concept; graphics and animation generations using
+AWT, JavaFX, Swing and Java2D; applets; sounds
+generations using Java Sound API; programming
+using Java Media Framework (JMF), Android
+Development ToolKit (ADT)
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wiG3004
+VIRTUAL REALITY
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the technology that support virtual
+reality applications and human perceptions
+involved in designing virtual reality environment.
+2. Discuss other technologies including
+visualization and augmented reality
+3. Develop a virtual reality environment using
+suitable tools and programming language
+‘Synopsis of Course Content
+This course begins with some introduction to virtual
+reality technology and its applications, followed by
+
+### Page 263
+detail explanation regarding input and output
+devices that are being used in virtual reality
+application. Students will also learn about human
+sensory systems (visual, audio and tactile) and
+their relations to the development of virtual reality
+devices, 2s well as the possible effects these
+devices have on human health. Then students will
+be taught about how to model a virtual reality world
+and manipulate its objects using virtual reality
+development tools and programming languages.
+The course ends by providing students with
+fundamental knowledge regarding data
+visualisation and augmented reality, a research
+area that is closely related to virtual reality, systems
+(visual, audio and tactile) and their relations to the
+development of virtual reality
+‘Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wiG300s
+GAME DEVELOPMENT
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+Explain the basic principles of computer games,
+game genre, game development life cycle and
+design consideration
+2. Develop a computer game taking into
+consideration selected game genre.
+3. Explain collision detection in game
+programming,
+Synopsis of Course Content
+This course will give an introduction to computer
+game development starting from concept
+development to implementation of a playable ame
+prototype. Both the aesthetic and technical aspects,
+of game development will be covered. The
+aesthetic component of the course will focus on
+story and character development, game
+mechanics, game play and interface design and
+content creation for games. The technical
+component of the course will focus on
+programming tools and concepts for games,
+including data structures & algorithms, computer
+graphics, human-computer interaction, shader
+programming and Al. Common topics include
+project management, prototype development and
+play testing. Students will work in groups and go
+through the complete pipeline starting from a basic
+game idea all the way through developing a
+playable prototype.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wiG3006
+DIGITAL VIDEO PROCESSING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain about the digital video processing
+techniques in specific.
+2. Differentiate the use of digital video processing
+‘techniques in several multimedia applications.
+3. Apply the appropriate digital video processing
+techniques,
+‘Synopsis of Course Content
+This course covers topics in digital video
+processing as follows: representation of digital
+video; spatial and temporal sampling; two and
+three dimensional motion estimation techniques;
+video coding techniques; stereo and multiview
+video processing: video compression methods and
+standards; and error control in video
+communications,
+Assessment Method
+Continuous Assessment: 50%
+Final Examination: 50%
+WIG3007
+SPECIAL TOPICS IN MULTIMEDIA
+Credit: $
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Identify the current and specific topics in
+multimedia science.
+2. Describe the technologies related to multimedia
+science.
+3. Apply the related new technologies to the
+design of multimedia applications.
+‘Synopsis of Course Content
+This course serves as a platform to deliver
+specialized topics in multimedia offered by
+interested lecturers and professionals. This course
+may run in any semester depending on the
+availabilty of the interested instructor and the
+demand from the students
+Assessment Methods
+Continuous Assessment: 50%
+
+### Page 264
+Final Examination: 60%
+wig3008
+MULTIMEDIA FORENSIC AND SECURITY
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instructio
+: English
+Learning Outcomes
+Identify forensic and security issues related to
+multimedia,
+2. Differentiate various elementary forensic
+techniques for multimedia content.
+3. Apply appropriate security techniques in
+multimedia content,
+Synopsis of Course Content
+This course is designed to provide students with
+knowledge on various digital media protection
+technology. Students will also be exposed to the
+different issues on cybercrime related to digital
+media. In addition, this course will discuss the
+different stages in the digital forensic process and
+various digital forensic techniques in accordance
+with the identified media and applicable cyber
+crime laws.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+‘WiE3010
+DATA VISUALIZATION
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain concepts and techniques relevant to
+data
+jie; data aspects, modeling
+concepts, and visualization techniques.
+3. Apply suitable visualization techniques to
+appropriate datasets.
+4. Use appropriate tools to analyze, and present/
+visualize data,
+Synopsis of Course Content
+This course begins by introducing the concepts of
+data visualization vs infographics. It provides
+students with the knowledge of where data can be
+found (data sources), how data can be acquired
+and how data can be analyzed and presented. It
+explains topics such as modeling concepts, data
+aspects, and visualization techniques. Techniques
+for visualizing multivariate, temporal, text-based
+geospatial, and other types of data are taught
+Students will be exposed to a few tools; to
+capture/import data, to analyze data and to
+visualize data,
+Assessment Method
+Continuous Assessment: 50%
+Final Examination: 50%
+wiF2003,
+WEB PROGRAMMING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+Use different programming languages,
+techniques, platforms and tools for web
+development.
+2. Use frameworks and database to develop web
+applications.
+3. Apply different techniques to improve the
+quality of web applications.
+Synopsis of Course Content
+This course covers the techniques, frameworks,
+platforms and tools for Web development.
+Theoretical aspects include the concepts of Web
+development, stack technologies, client-server
+architecture, and quality attributes of Web-based
+systems. Technical aspects include topics on
+design and development of web database
+applications using different protocols, programming
+languages, techniques, frameworks, platforms and
+tools, taking relevant quality issues into
+consideration’
+Assessment Method
+Continuous Assessment: 50%
+Final Examination: 50
+
+
+## Shared Undergraduate Curriculum :: Specialization Elective Courses - Data Science
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 265-268
+
+### Page 265
+a
+COURSE
+INFORMATION
+SPECIALIZATION
+ELECTIVE COURSES
+DATA SCIENCE
+Ay A
+
+### Page 266
+‘wiH2001
+DATA ANALYTICS
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the basic concepts of data analytics
+2. Differentiate the various data analytics
+techniques.
+3. Apply the appropriate data analytics
+techniques.
+Synopsis of Course Content
+This course aims to develop students’ ability to
+describe, explore and analyze data using suitable
+data analytics techniques.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+wiD2001
+KNOWLEDGE REPRESENTATION AND
+REASONING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Describe different kinds of knowledge and their
+related engineering processes.
+2. Explain the various knowledge representation
+and knowledge reasoning methods.
+3. Use the various knowledge representation and
+knowledge reasoning methods to solve
+problems
+Synopsis of Course Content
+This course describes the different kinds of
+knowledge and their related engineering processes.
+It explains the various knowledge representations
+methods such @s tule-based, frame-based,
+case-based reasoning, semantic network, script,
+conceptual graph and ontology. It also explains the
+various knowledge reasoning methods such as the
+deductive, inductive, monotonic and non-monotonic
+reasoning. Students will use the various knowledge
+representation and knowledge reasoning methods
+to solve problems.
+Assessment Methods
+Continuous Assessment: 50%.
+Final Examination: 50%
+wib2002
+COMPUTING MATHEMATICS II
+Credit: 3
+Course Pre-requisite(s): None
+Medium of instruction: English
+Learning Outcomes
+1. Apply various formulae for operations on
+differentiation and integration as well as various
+matrix algebra.
+2. Solve problems involving various types of
+mathematical transformations.
+3. Apply statistical methods and sampling in
+problem solving.
+‘Synopsis of Course Content
+This course covers important mathematics topics
+which can be applied to artificial intelligence field
+The topics include calculus (differentiation and
+integration), functions and graphs, matrix algebra
+(Eigen value, Eigen vector, dependency,
+singularity), statistical methods (sampling, principle
+component analysis) and transformations (Fourier,
+Laplace, Hough, geometric and wavelet)
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+‘wiD3001
+FUNCTIONAL AND LOGIC PROGRAMMING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Describe basic principles and features of
+functional and logic programming.
+2. Explain concepts and methods of functional and
+logic programming.
+3. Apply functional and logic programming
+knowledge.
+Synopsis of Course Content
+This course introduces Artificial Intelligence (Al)
+programming languages, which covers functional
+and logic styles of programming. It describes the
+functional programming that uses functions as its
+basis and includes topics such as types and
+classes, lists, recursions, and higher-order
+functions. The logic programming is based on
+formal logic and includes topics such as clauses
+and predicates, unification, operators. and
+arithmetic, cuts and negation.
+Assessment Methods
+Continuous Assessment: 50%
+
+### Page 267
+Final Examination: 60%
+wip3002
+NATURAL LANGUAGE PROCESSING
+Credit: 3
+Medium of Instruction: English
+Learning Outcomes
+1. Identify the levels of natural language
+processing.
+2. Describe the natural language processing
+techniques.
+3. Apply basic algorithms of natural language
+processing.
+Synopsis of Course Content
+The course introduces the theory and methods of
+Natural Language Processing (NLP). It covers a
+broad range of topics in NLP including basic text
+processing, minimum edit distance, syntactic
+analysis, and semantic analysis. In addition, it also
+cusses some NLP applications such as machine
+translation and automatic summarization
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 60%
+WIE3007
+DATA MINING AND WAREHOUSING
+Credit: 3
+Course Pre-requisite(s): None
+Medium of Instruction: English
+Learning Outcomes
+1. Explain the concept of Data Mining and Data
+Warehouse.
+2. Create a schema diagram for the data
+warehouse using Star schema.
+3. Develop model using various data mining
+techniques
+Synopsis of Course Content
+The course consists of the following components:
+(a) Introduction to Data Warehouse and Data
+Mining; (b) Data Warehouses; (c) Pre-mining: (d)
+Classification: (e) Association Rules; (f) Clustering
+Algorithms.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 50%
+WIE3008
+BUSINESS ANALTYTICS AND INTELLIGENCE
+Credit: 3
+Course Pre-requisite(s): WIA2001 Database
+Medium of Instruction: English
+Learning Outcomes
+4. Explain the concept of 8! and implementation of
+Date warehouse
+2. Integrate data from different sources.
+3. Use suitable methods and techniques to
+analyse OLAP data to solve business problems.
+Synopsis of Course Content
+This course discusses Online analytical processing
+(OLAP), Data warehouses and data Dimensional
+modelling, Extract Transform Load (ETL) design,
+and statistical and mining approaches to improve
+business. It also covers report design, development
+and emerging trends in business intelligence.
+Assessment Methods
+Continuous Assessment: 70%
+Final Examination: 30%
+WIE3010
+DATA VISUALIZATION
+Credit: 3
+Course Pre-requisite(s) : None
+Medium of Instruction: English
+Learning Outcomes
+Explain concepts and techniques relevant to
+data visualization, i.e.; data aspects, modeling
+concepts, and visualization techniques.
+2. Apply suitable visualization techniques to
+appropriate datasets.
+3. Use appropriate tools to analyze, and
+presentivisualize data.
+Synopsis of Course Content
+This course begins by introducing the concepts of
+data visualization vs infographics. It provides
+students with the knowledge of where data can be
+found (data sources), how data can be acquired
+and how data can be analyzed and presented. It
+explains topics such as modeling concepts, data
+aspects, and visualization techniques. Techniques
+for visualizing multivariate, temporal, text-based
+geospatial, and other types of data are taught
+Students will be exposed to a few tools; to
+capture/import data, to analyze data and to
+visualize data,
+Assessment Methods
+Continuous Assessment: 50%
+
+### Page 268
+Final Examination: 60%
+WIH3003
+BIG DATA APPLICATION AND ANALYTICS
+Credit: 3
+Course Pre-requisite(s) : None
+Medium of Instruction: English
+Learning Outcomes
+1. List the concepts of Big Date Applications and
+Analytics.
+2. Explain suitable methods and techniques to
+collect and analyse big data
+3. Use big data in real worid problem solutions.
+Synopsis of Course Content
+The course will cover a) Big data applications and
+analytics, b) Data Collection, Sampling and
+Preprocessing, ¢) Predictive Analysis, d)
+Descriptive analysis, ¢) Survival analysis, f) Social
+networks analysis, g) Case study of Big Data
+Applications.
+Assessment Methods
+Continuous Assessment: 70%
+Final Examination: 30%
+‘WIH3004
+‘TRENDS IN DATA SCIENCE
+Credit: 3
+Course Pre-requisite(s) : None
+Medium of Instruction: English
+Learning Outcomes
+1. Describe emerging computer technologies,
+data science technique, industry applications,
+and current trends in data science.
+2. Discuss critical issues related to managing
+data and technologies.
+3. Apply tools or model to relevant cases or data,
+Synopsis of Course Content
+This course explores selected topics of specialized
+content (not usually covered by the other courses)
+as determined by the department and the lecturer
+with emphasis on current data science trends.
+Topics under this course heading vary from year to
+year according to the developments in computer
+technology and information systems.
+Assessment Methods
+Continuous Assessment: 50%
+Final Examination: 60%
+
+
+## Industrial Training :: Industrial Training Guidelines
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 270-280
+
+### Page 270
+INTRODUCTION
+Industrial Training is a training program that is compulsory for students of Bachelor of Computer
+Science from the Faculty of Computer Science and Information Technology (FCSIT), Universiti
+Malaya. The purpose of this training is to give exposure to students on the operations and real
+activities in the workplace.
+Through Industrial Training, students will be able to see how the concepts of Computer Science
+and Information Technology learnt in university can be practiced in development processes and
+daily management of an organization. It will also increase and improve skills that are needed by
+students with the guidance of professionals from industry and University. In relation to that,
+Industrial Training plays the role as the preparation point that allows a student to get involved in a
+profession related to his or her field of study.
+This
+guideline
+can
+be
+used
+as
+a
+reference
+by
+Industrial
+Training
+Committee,
+organizations/companies, Company Supervisors, Faculty Supervisors and students. It provides
+guidelines related to the functions or roles that all parties involved in the Industrial Training should
+play; the training scope required as well as the ways evaluations are carried out.
+DEFINITION OF INDUSTRIAL TRAINING
+Industrial Training is the training undergone by students in any organization/company which
+provides tasks related to the field of Computer Science for a determined period to obtain working
+experience by practicing what was learnt in university.
+AIM OF INDUSTRIAL TRAINING
+The aim of Industrial Training is to enable students to get experience in related
+organizations/companies in parallel with the faculty’s intention to produce graduates with skills
+and specializations to fulfil the country’s current needs.
+OBJECTIVES OF INDUSTRIAL TRAINING
+1.
+2.
+3.
+4.
+To produce excellent graduates who are always open-minded, innovative, smart in
+communicating and competitive.
+To expose students to the real situation of operation, development and management
+processes in the workplace.
+To provide opportunities to students to participate as members in completing a task or
+development project.
+To provide experience to students in learning techniques to solve problems faced during work
+and to contribute innovative ideas to the organizations.
+To allow students and University to get exposure to the latest systems and technologies used
+by the external organizations.
+- - - - - INDUSTRIAL TRAINING
+FACULTY OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGY
+UNIVERSITI MALAYA
+
+### Page 271
+IMPLEMENTATION
+Industrial Training Committee
+The Industrial Training Committee of FCSIT is appointed by the Dean for a given timeframe. It
+consists of Industrial Training Coordinator from each department or unit in the faculty. A
+Department Industrial Training Coordinator is in-charge of the Industrial Training of the students of
+its department. The committee is led by the Head of Coordinator and is assisted by a support staff
+for clerical matters.
+The tasks of the Industrial Training Committee are:
+Industrial Training Time and Duration
+The eligible students must undergo their Industrial Training in Semester 1 ofYear 3, for a duration
+of 24 weeks.
+In certain cases, the Faculty can approve students to undergo Industrial Training at another
+Semester instead of Semester 1 of Year 3.
+5.
+5.1
+5.2
+Plan, implement and coordinate Industrial Training programme.
+Prepare guidelines and related information.
+Coordinate Industrial Training programme at the Faculty with Centre for Integral Learning
+(CITrA), Universiti Malaya.
+Determine the scope of Industrial Training as a guideline for students and employers.
+Identify forthcoming students for Industrial Training and ensure that they are registered.
+Ensure the Industrial Training regulations in the curriculum are conformed.
+Give briefing to the forthcoming Industrial Training students.
+Identify organizations that are suitable for students’ placement.
+Ensure that students get the insurance application form, Industrial Training confirmation form,
+and other relevant documents from CITrA.
+Advertise, promote and encourage students to attend preparatory workshop conducted by
+CITrA Send and monitor students at the organizations/companies during the Industrial
+Training.
+Appoint lecturers from FCSIT as Faculty Supervisors to supervise each student undergoing
+Industrial Training.
+Monitor the students’ welfare during Industrial Training.
+Develop and update the evaluation method.
+Collect, check, coordinate and present the students’ Industrial Training results to the Deputy
+Dean (Undergraduate).
+- - - - - - - - - - - - - - To provide opportunities for organizations and industry to train and identify the potential of
+future graduates of university.
+To get feedback to continuously improve the quality of the courses offered by the faculty.
+To motivate students to improve their academic achievements after undergoing Industrial
+Training.
+- - -
+
+### Page 272
+Student Requirements
+Industrial Training is COMPULSORY for all Bachelor of Computer Science students who are listed
+as eligible. Eligible students:
+Requirements of Organisations/Companies
+As the measure to ensure that organisations/companies offering Industrial Training provide
+suitable training in the field of Computer Science, the Faculty has set some criteria that must be
+fulfilled by any of the interested organizations/companies, namely:
+Training Scope
+Organizations/companies offering Industrial Training to the students MUST be able to train them
+in the practical aspects of Computer Science. The suggested job scopes include, but not limited
+to:
+Other than that, organizations/companies have the responsibility to provide students with the
+opportunity to enhance their soft skills.
+Students’ Responsibilities
+5.3
+- - - The organizations/companies MUST offer job specifications within the scope stated in
+Section 5.5. Jobs and tasks that focus only on sales, teaching, administration and the like,
+are NOT allowed.
+The organizations/companies MUST offer formal working hours and office environment only.
+Teleworking, virtual office and so on, are NOT allowed unless being specifically specified in
+the offer letter (for example remote internship). Students are allowed to work on night shift if it
+is the instruction from the companies and it follows the companies’ safety guidelines for
+workers.
+It is NOT compulsory for the organizations/companies to provide allowances or honorarium to
+the students but are highly encouraged to do so to help students in coping with living
+expenses.
+Become a member of a system development project: conduct feasibility study, analysis,
+design, implementation, maintenance and evaluation.
+Formulate problem solution and programming in information management system
+development, web access, computer network control, and research and development.
+Hands-on experience in developing, testing, and deploying AI models, understanding ethical
+AI practices
+Practical experience in data analysis, visualization, and interpretation, proficiency in using
+data science tools and programming languages.
+Hands-on experience in system design, implementation, and troubleshooting, familiarity with
+hardware and software integration, exposure to network management, cybersecurity
+practices.
+Practical experience in digital content creation, graphic design, video production, and
+interactive media development.
+Must have taken all Faculty and Programme Core Courses (except Academic Project I and
+Academic Project II).
+Must not register Industrial Training together with any other courses in one semester.
+- - - - - - Identify and apply directly to suitable organizations/companies for Industrial Training
+placement one semester before the Industrial Training Programme for local placement, and
+at least two semesters before the Industrial Training Programme for abroad placement. Refer
+to Section 5.7.
+- - - 5.4
+5.5
+5.6
+
+### Page 273
+- - - - - - - - - - - - - - - - - - - - - - - Should not undergo Industrial Training in an organization/company where there might be
+conflict of interests, such as, in an organization/company owned by one's own family or
+relative, organization/company where the student has worked before or is currently working,
+and so on.
+FCSIT students are not allowed to undergo Industrial Training in Universiti Malaya including
+spin-off companies, except for certain cases which are approved.
+Get the advice from the Industrial Training Coordinator if unsure of the suitability of an
+organization/company.
+Inform the Industrial Training Coordinator if unable to get a placement for Industrial Training
+and ready to accept a training place decided by the Industrial Training Coordinator.
+Attend a briefing related to Industrial Training.
+Required to attend a total of 4 hours preparatory workshops organized by CITrA and/or the
+faculty, before Industrial Training.
+Choose only ONE place for Industrial Training.
+Email offer letter to Industrial Training Department Coordinator to get approval for the
+placement before starting the training. The offer letter must state the start and end dates of
+the Industrial Training of the student, the tasks in general that will be assigned to the student
+during the training, and the department where the student will be placed. Without this
+information the placement will not be approved by the Industrial Training Department
+Coordinator.
+The student is responsible to make sure that the duration of the student’s Industrial Training
+is at least 24 weeks. If less than 24 weeks, the student does not fulfil the requirement of the
+Industrial Training programme and will fail his or her Industrial Training.
+Register the internship placement in Maya and the career portal and submit all the required
+documents including the offer letter.
+Get written permission from the Faculty to withdraw from the Industrial Training programme
+or to change the location of placement or to reject an offer accepted previously.
+Follow the training requirements.
+Carry out the tasks and the responsibilities assigned by the organization/company under the
+supervision of one or more Company Supervisors.
+Adhere to all the rules and regulations of organization/company as long as not contradicting
+with the rules of the University.
+Always be positive and give the best contribution in carrying out the tasks given.
+Carry out Industrial Training in an ethical and professional manner and uphold the good
+name of the University at all times.
+Contact and inform Industrial Training Coordinator/Faculty Supervisor immediately if facing
+any problem.
+Record all activities that have been carried out in Logbooks and submit to the Faculty
+Supervisor via the career portal following the schedule in Section 5.8.
+Write the Industrial Training Final Report and conduct other tasks assigned.
+Contact the appointed Faculty Supervisor to arrange for the supervisor to visit the student at
+the organization/company where the student is undergoing his or her Industrial Training. A
+student who fails to do so before the end of his or her Industrial Training will fail Industrial
+Training.
+Be present at the training place during the Faculty Supervisor’s visit and conduct a
+presentation and demonstrate devices or systems that have been used or learnt.
+Show the Logbook to be checked by the Faculty Supervisor during the supervisor’s visit.
+Adhere to the Industrial Training rules and regulations set by the Faculty, CITrA, and the
+University.
+
+### Page 274
+- - aa)
+Leave taken during Industrial Training has to be replaced (even though it is the student’s
+entitlement, and the organization/company has approved it) unless the student obtains a
+letter from the organization/company which states that it is unable to let the student to
+replace the leave. Include this letter in the Final Logbook. Sick leave which has been
+approved by the organization/company does not need to be replaced. Include the medical
+certificate and Company Supervisor's approval on the sick leave in the Logbook.
+Always visit CITrA website and Industrial Training website of the Faculty to get the latest
+information.
+Perform the required actions following the schedule in Section 5.8.
+
+### Page 275
+5.7 Flow Chart for Applying Industrial Training Placement
+Start
+GRE TNT
+‘rieting and
+preparatory
+workshops.
+Apply to organization
+Search for intemship
+by sending resume Je
+‘and referral letter ‘organization
+Being
+oftered
+a place?
+Obtain otter teter Overseas
+rom the organization Internship? No
+Yes
+Discussion wih company he
+‘supervisor and department
+‘covedinator about suitably
+‘ofthe intemship placement
+country?
+Seek approval ror
+|coordinator about the
+internship placement
+Yes Yes
+¥ ¥
+[Seek assistance trom
+Sipctiatlnstertnd ‘academic advsor for
+placement in Maya TRAN COSA Ten.
+Y Y
+‘Sox approval ror
+Sua rip to
+paced te. anya coer
+[FSKTM career poral ens postpone
+"7
+Inform depariment
+coordinator for
+ntemship placement
+‘approvalin Maya
+Maya couse
+registration
+a
+End +———
+
+### Page 276
+5.8 Students’ Schedule
+5.8.1 During Industrial Training
+Note: The week in the tables above refers to the week of a student’s Industrial Training
+and not the week of the semester.
+
+### Page 277
+5.9
+5.10 Faculty Supervisors’ Schedule
+Week
+Tasks
+1. Receive letter of appointment of supervision from TDID office.
+2. Receive Plan of Tasks in the career portal.
+Receive First Logbook (comprising Week 1 to 8) from the student
+in the career portal.
+Assess the First Logbook using Evaluation Form 1A (10%) in the
+career portal.
+Receive Second Logbook (comprising Week 9 to 16) from the
+student in the career portal.
+Assess the Second Logbook using Evaluation Form 1A (10%) in
+the career portal.
+Visit the student at the respective company and assess the student
+including the Logbook by using Evaluation Form 1B (20%) in the
+career portal. The marks given for Evaluation Form 1B can be
+finalized after returning from the visit and the marks should not be
+released to the student or organisation/company.
+Receive Final Report and Final Logbook in the career portal.
+Assess the Final Report and Final Logbook of each student
+assigned by using Evaluation Form 1C (20%) in the career portal.
+Faculty Supervisors’ Responsibilities
+10 - 11
+18 - 19
+21 - 24
+Within two
+weeks after
+submission of
+Final Report.
+Note:
+1.
+Ensure that students undergo the Industrial Training in-line with the objectives
+established.
+Assist in solving students’ problems related to the field of work.
+Arrange for at least one visit to the organisation/company within Week 21 to 24 of the
+student’s training.
+Visit the company to give advice to the student, meet the Company Supervisor, assess
+the suitability of the company for students, and evaluate the student.
+Evaluate the student progressively following the schedule in Section 5.10.
+Inform about the company supervisor evaluation to the Company Supervisor.
+Coordinate the marking and submit the marks and all the evaluation forms to the
+Industrial Training support staff.
+Provide suggestions to improve future Industrial Training program.
+Perform the required things following the schedule in Section 5.10.
+The week in the table above refers to the week of a student’s Industrial Training
+and not the week of the semester.
+All the evaluation forms are accessible in the career portal of FCSIT.
+2.
+- - - - - - - - -
+
+### Page 278
+5.11 Organisation/Company’s Responsibilities
+5.13 Organisation/Company Supervisors’ Schedule Tasks
+Week
+Before
+Industrial
+Training
+5.12 Organisation/Company Supervisors’ Responsibilities
+1 - 2
+1 - 8
+Verify the student’s Logbook on a weekly basis. The student has
+to submit First Logbook (comprising Week 1 to 8) to the Faculty
+Supervisor in the career portal by Week 9.
+1.If your organisation/company had been registered with a career
+portal, watch out for emails from the system on students’
+applications to undergo Industrial Training at your organisation
+and approve those applications that you want to accept.
+2.Issue offer letters to students you want to accept. The offer
+letter must state the start and end dates of the Industrial
+Training of the student, the tasks in general that will be
+assigned to the student during the training, and the department
+the student will be placed. Without this information the
+placement will not be approved by the faculty.
+Sign Confirmation Form passed to you by the student.
+Refer to the career portal of FCSIT or the student, to get the
+template for the Plan of Tasks, the name and email of the
+supervisor from the faculty that has been assigned to the student,
+and the name and email of the Industrial Training support staff.
+- Supervise the student for the whole duration of the Industrial Training.
+- Perform the required things following the schedule in Section 5.13.
+- Inform the Industrial Training Coordinator/Faculty Supervisor of any problem or issue
+in relation to Industrial Training.
+Tasks
+Identify the number of students needed, specialisation, and job specification.
+State the following information in the offer letter for the student: the start and end dates of
+the Industrial Training of the student, the tasks in general that will be assigned to the
+student during the training, and the department the student will be placed. Without this
+information the placement will not be approved by the faculty.
+The duration of Industrial Training for FCSIT students is 24 weeks. If less than 24 weeks,
+the student does not fulfil the requirement of the Industrial Training programme and will fail
+his or her Industrial Training.
+Please take note that 24 weeks is not equivalent to 6 months.
+Appoint one of its officers as Company Supervisor to the student throughout the student’s
+Industrial Training.
+Determine the student’s training scope in accordance with the University’s suggestion.
+Provide appropriate exposure in order for the student to obtain useful practical experience.
+Provide facilities relevant to the tasks given to the student.
+Consider giving appropriate allowance or honorarium to students undergoing Industrial
+Training. The giving of allowance or honorarium is not mandatory but highly encouraged to
+help students in coping with living expenses.
+Give feedback to the Industrial Training Coordinator/Faculty Supervisor regarding training
+given.
+- - - - - - - - -
+
+### Page 279
+9 - 16
+Verify the student’s Logbook on a weekly basis. The student has
+to email scanned Second Logbook (comprising Week 9 to 16) to
+the Faculty Supervisor in the career portal by Week 17.
+Verify the student’s Logbook on a weekly basis. The student has
+to submit the Final Logbook (comprising all the weeks) together
+with the Final Report in the career portal within one week after the
+training ended.
+Allocate time to meet the Faculty Supervisor during his/her visit of
+the student at the company.
+1. Complete Evaluation Form 2A (40%) to assess the student
+performance in the career portal. The marks given in the
+evaluation form are confidential and should not be released to
+the student.
+17 - 24
+21 - 24
+2. Verify the Final Report and Final Logbook prepared by the
+student for submission to the Faculty.
+3. Receive a copy of the Final Report from the student.
+4. Complete the Industrial Training Survey online.
+Note: The week in the table above refers to the week of the student’s Industrial Training
+and not the week of the semester.
+Student Placement Process
+Refer to the latest guideline provided by CITrA and Section 5.7.
+EVALUATION
+Purpose of Evaluation
+The purposes of evaluation are to:
+- - - Student Evaluation Criteria
+There are TWO (2) main aspects of evaluation:
+- - Measure the student’s job/training performance and the quality of the student’s work.
+Evaluate the development of the student’s character.
+Guide the student’s training.
+Job performance evaluation; and
+Student character evaluation.
+5.15
+6.1
+6.2
+
+### Page 280
+7.
+8.
+9.
+6.3 Evaluation Method
+Evaluation is done continuously and involves the Faculty Supervisor and Company
+Supervisor. The following table shows the details of the evaluation:
+Content
+Week 1 to 8
+Week 9 to 16
+All the weeks
+LOGBOOKS PREPARATION AND SUBMISSION
+Percentage
+Submission Date
+5pm, Friday of Week 9
+5pm, Friday of Week 17
+Within two weeks after training ended
+Evaluator
+Faculty Supervisor
+Faculty Supervisor
+Faculty Supervisor
+Company Supervisor
+Faculty Supervisor
+First Logbook
+Second Logbook
+Presentation during Faculty
+Supervisor’s visit
+End of Training Evaluation
+Final Report and Final Logbook
+First Logbook
+Second Logbook
+Final Logbook
+Note: The week in the table above refers to the week of a student’s Industrial Training
+and not the week of the semester.
+FINAL REPORT PREPARATION
+CONCLUSION
+Through the Industrial Training programme, the Faculty and University truly hope that
+students can make use of the provided opportunities to improve their knowledge and
+skills before embarking on their careers.
+Final Report must be prepared according to the format given at the Industrial Training
+Website of FCSIT.
+Refer to the guideline of writing the Final Report at the Industrial Training Website of
+FCSIT.
+Final Report must be verified by the Company Supervisor to ensure the authenticity of
+the information before submission.
+Final Report must be submitted to the Industrial Training support staff in the career
+portal and to the company within one (1) week after the Industrial Training ended.
+- - - - Every student is required to prepare the following Logbooks to record all the daily activities in the
+organisation/company:
+The Logbooks must be prepared following the template given at the Industrial
+Training Website of FCSIT.
+- -
+
+
+## Academic Project :: Academic Project I and II Guidelines
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 282-289
+
+### Page 282
+1. Introduction
+An Academic Project (AP) is a project or academic task that must be accomplished
+individually by every undergraduate student to obtain the attributions. It is compulsory for
+students of Bachelor of Computer Science from the Faculty of Computer Science and
+Information Technology (FCSIT), Universiti Malaya.
+ACADEMIC PROJECT I AND II
+FACULTY OF COMPUTER SCIENCE AND INFORMATION TECHNOLOGY
+UNIVERSITY OF MALAYA
+The list of the courses of Academic Project is divided as follows:
+Pass all Faculty and Programme Core Courses except for Industrial Training and
+Academic Project II.
+This guideline is produced with the purpose of becoming the reference and guide to the
+Academic Project Committee, supervisors, panels, and students. It provides guidelines
+related to the functions or roles that all parties involved in the Academic Project carry out.
+FCSIT offers Academic Project I and Academic Project II to final year students in order to
+produce quality graduates who are excellent and academically competent in the field of
+Computer Science. The aim of these courses is to leverage students’ technical and soft
+skills gained throughout their studies. Students should be able to demonstrate their
+technical knowledge, problem-solving, critical thinking, and good decision-making while
+researching, developing, and completing the project.
+No.
+Course
+Title
+Academic
+Project I
+Programme
+Credits
+Semester
+Semester II
+Year 3
+1.
+2.
+Academic
+Project II
+Bachelor of Computer Science
+Bachelor of Information Technology
+Bachelor of Computer Science
+Bachelor of Information Technology
+Semester I
+Year 4
+Pre-requisite: Bachelor of Computer Science - WIA3002
+Course
+Code
+WIA3002*
+WIB3002*
+WIA3003#
+WIB3003#
+
+### Page 283
+2. Course Outcome
+No. Course Title
+3. Roles and Responsibilities
+Academic Project Committee
+The Academic Project Committee of FCSIT is appointed by the Dean for a given timeframe. It
+consists of an Academic Project Coordinator from each department or unit in the faculty. A
+Department Academic Project Coordinator is in-charge of the academic project matters of the
+students of the department. The committee is led by the Head of Coordinator and is assisted
+by a support staff for clerical matters.
+Course Outcome
+1.
+2.
+Academic
+Project I
+Academic
+Project I
+At the end of the course, students are able to:
+1. Discuss the software development life cycle for the project
+implementation.
+2. Develop a system based on the problems identified.
+3. Write an academic project report undertaken by the project.
+4. Experiment with the developed product.
+The tasks of the Department's Academic Project Coordinator are managing the process of
+Academic Project I and Academic Project II as follows:
+Approve project titles from the supervisor via the ilmiah system.
+Assign panels for monitoring and viva sessions via the ilmiah system.
+Arrange viva schedules.
+Inform panels, supervisors, and students on the Viva schedules via the ilmiah system.
+Submit report on student marks for Academic Project I to Head Coordinator.
+Generate reports on students' viva marks via the ilmiah system.
+Moderate marks for Academic Project 1.
+At the end of the course, students are able to:
+1. State the problem background.
+2. Identify a solution approach that is suitable for the
+stated problem.
+3. Report a literature review that is related to the stated
+problem.
+4. Conduct suitable data gathering techniques.
+5. Write a project proposal.
+
+### Page 284
+Panel
+Students
+Supervisor
+Enter the project titles via the ilmiah system.
+Assign students to the project via the ilmiah system.
+Supervise and coach students on the project.
+Regular meetings with students for project discussion (at least 7 times of
+meetings/discussions per semester).
+Verify student’s progress logbook.
+Evaluate the student’s report.
+Enter student’s marks via the ilmiah system.
+Register for the course.
+Attended the briefing on the Academic Project by the Head Coordinator (Week 1).
+Consult and confirm project supervisor (Week 1 – Week 2).
+Confirm the project titles in the ilmiah system (Week 2).
+Attend the preparatory workshops.
+Have regular meetings with the supervisor for project discussion.
+Compulsory to summarize the outcome of discussion/meetings with the supervisor
+in the progress logbook.
+Submit progress logbook to supervisor for verification (Week 7 & Week 13).
+Submit presentation slides, presentation video and progress logbook for
+monitoring in the ilmiah system.
+Submit presentation slides, presentation video and progress logbook for
+viva in the ilmiah system.
+Attend the viva session as scheduled.
+Evaluate student’s project progress for monitoring.
+Enter student’s monitoring marks in the ilmiah system.
+Attend student’s viva session for Academic Project I and Academic Project II.
+Evaluate student’s project development, technical skills, system demonstration and
+soft skills.
+Enter student’s marks in the ilmiah system.
+
+### Page 285
+Submit the final report in the
+Figure 1 represents Academic Project
+supervisor, panel and coordinators.
+system.
+Figure 2 represents Academic Project II process flow. The processes involve the
+student, supervisor, panel and coordinators.
+I process flow. The processes involve student,
+#The submission date for all materials prepared for the monitoring session, viva session and
+academic project report will be notified via the ilmiah system by the Department Coordinator.
+ilmiah
+4. Academic Project I Process Flow
+5. Academic Project II Process Flow
+
+### Page 286
+Section
+6. Academic Project I Report
+A title should reflect the project. The title must be concise and
+well-written to give a general overview of what the project is
+all about.
+An abstract of the whole report including objective, method,
+findings, and discussion. The abstract must not exceed 300
+words.
+Lists all section headings, subsection headings, figures, and
+tables with page numbers.
+In the body of the report, a student must address the following
+information:
+Abstract
+Title Page
+Conclusion
+References
+Appendices
+(if appropriate)
+Table of Contents
+Substantive body of the
+report
+Each student is required to prepare and submit a report for Academic Project I. The report
+must contain the following information:
+Chapter 1:
+- Introduction to relevant project/title: In the introduction,
+students must introduce the subject of the project. It
+should give some insight into the structure of the
+report. Some general remarks including problems and
+existing works must be included.
+- Problem statements
+- Project objectives (and module objectives if it is a group
+project)
+- Project timeline
+ii.
+iii. Chapter 3: Research methodology
+iv. Chapter 4: System analysis and design (Project
+requirements and initial design)
+A conclusion is a summarization of the main points of the
+project and the gap(s) that is/are able to solve.
+Details of published sources of material referred to or quoted
+in the text (including any lecture notes and URL addresses of
+any websites used). Provide up-to-date references (5 years
+back). Use APA reference style.
+Any further material which is essential for full understanding
+of the report (e.g. large scale diagrams, survey questions,
+raw data, specifications).
+Chapter 2: Literature review
+i.
+Details
+
+### Page 287
+Section
+7. Academic Project II Report
+Abstract
+Title Page
+Conclusion
+References
+Appendices
+(if appropriate)
+Acknowledgment
+Table of Contents
+Introduction
+Substantive body of the
+report
+Each student is required to prepare and submit a report for Academic Project I. The report
+must contain the following information:
+Details
+A title should reflect the project. The title must be concise
+and well-written to give a general overview of what the
+project is all about.
+An abstract of the whole report including important features,
+results, and conclusions. The abstract must not exceed one
+(1) page.
+List of individuals who are involved in the project either
+directly or indirectly.
+Lists all section headings, subsection headings, figures, and
+tables with page numbers.
+States the objectives, problem, methodology, implementation,
+results, and discussion.
+In the body of the report, a student must address the
+following information:
+The contents of Project Academic I report.
+Chapter 4: System analysis and design (details analysis and
+design)
+Chapter 5: System Development
+Chapter 6: Results and Discussion
+Chapter 7: Strengths, limitations and future works
+A summarization of the theme(s) developed in the main
+text.
+Details of published sources of material referred to or quoted
+in the text (including any lecture notes and URL addresses of
+any websites used). Provide an up-to-date reference (5 years
+back). Use APA reference style.
+Any further material which is essential for full understanding
+of the report (e.g. large scale diagrams, computer code, raw
+data, specifications).
+
+### Page 288
+8.
+9.
+No.
+Evaluation
+Plagiarism
+As an enrolled student at the University of Malaya, he/she is expected to produce original
+work. Any student who is found to have plagiarized his/her report that is part of the
+assessment in the academic project may be subjected to disciplinary action under the
+University of Malaya (Discipline of Students) Rules 1999.
+Course Title
+Assessment Component
+Total
+Total
+100%
+10%
+50%
+40%
+100%
+Weightage
+10%
+50%
+40%
+Assessor
+1.
+2.
+Academic
+Project I
+Academic
+Project II
+Monitoring
+Viva
+Report
+Monitoring
+Viva
+Report
+Grade
+Refer to the University’s Grading Scheme
+Panels
+Panels
+Supervisor
+Panels
+Panels
+Supervisor
+The assessment and the weightage assigned to each component are as follows:
+Continuous Assessment: 100%
+The assessment is divided into 3 parts which are monitoring, viva and report evaluation.
+Both monitoring and viva evaluation are performed by the appointed panels from each
+department. The report evaluation is performed by the project supervisor.
+Student’s soft skills are evaluated in the viva and report parts.
+# Important: A student will FAIL his Academic Project if
+he/she fails his viva. The student’s report is not evaluated for grading.
+he/she failed to attend the scheduled viva session. he/she did not
+present his/her project during the viva session.
+
+### Page 289
+10. Excellence Academic Project Award (APAC)
+steer the competition sprits amongst students to produce good/quality systems.
+acknowledge the effort of the students in designing and developing good systems.
+identify good projects for other students’ references and exhibitions.
+promote good projects for competitions, exhibitions, and intellectual property (IP).
+The Excellence Academic Project Award (APAC) was initiated in 2012 to motivate students to
+produce excellent projects. It is an annual event to select the best academic project of each
+department and unit. The event will be conducted during Week 15 of Semester I in every
+session. The objectives of APAC are to:
+
+
+## Language Path and English Communication :: Language Path Course / English Communication Programme 2025/2026
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 292-296
+
+### Page 293
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+
+### Page 294
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+
+### Page 295
+‘Depes8 WIM LZOLLIO Ssed#
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+### Page 296
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+
+
+## Student Dress Code :: Dress Code and Appearance Guides for Universiti Malaya Students
+
+- scope_label: general
+- source_doc: Complete Handbook
+- pages: 297-298
+
+UM STUDENT DRESS CODE AND APPEARANCE POSTER SUMMARY
+
+Compliance message
+- All Universiti Malaya students must adhere to the Universiti Malaya Administrative Directions (Student Dress Code and Appearance) 2024 while on campus.
+
+Illustrated attire categories on the poster
+- Official Events: the poster illustrates formal or traditional formal attire for official university occasions.
+- Lectures, Office Matters, Examination and Library: the poster illustrates neat, presentable campus attire for normal academic and administrative settings.
+- Sports and Recreational: the poster illustrates sportswear for sports and recreational activities.
+
+Enforcement and action
+- Academic, administrative, library and security staff members are authorised to reprimand students verbally or in writing if they violate the Administrative Directions.
+- A student who does not comply may be prevented from entering or dealing in areas where the provisions apply.
+- Other administrative actions may also be taken from time to time.
+
+Important limitation
+- This poster illustrates categories of appropriate attire and enforcement expectations, but it does not provide an exhaustive item-by-item prohibited clothing list.
+
+
+## Undergraduate Rules and Regulations :: Examination Honesty and Discipline / Undergraduate Rules
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 299-300
+
+### Page 300
+UNDERGRADUATE RULES AND REGULATIONS
+UNIVERSITY OF MALAYA (BACHELOR’S DEGREE) RULES & REGULATIONS 2019
+https://fsktm.um.edu.my/undergraduate-rules-amp-regulation
+STUDENT MISCONDUCT IN EXAMINATION
+https://aasd.um.edu.my/student-misconduct-in-examination
+ACADEMIC DISHONESTY - UNIVERSITI MALAYA ACADEMIC PROGRAMME
+MANAGEMENT POLICY
+https://aasd.um.edu.my/academic-dishonesty
+UNIVERSITI MALAYA (STUDENTS DISCIPLINE) RULES 1999
+https://hep.um.edu.my/disciplinary
+ZERO TOLERANCE CODE OF EXPLOITATION, ABUSE AND SEXUAL HARASSMENT
+IN UNIVERSITY MALAYA (UM)
+https://umintegrity.um.edu.my/news/are-you-harassed-exploited-or-sexually-abused
+TRANSFER CREDIT
+https://fsktm.um.edu.my/fsktm/doc/undergraduate/TK2UNIVERSITI%20MALAYA
+%20GUIDELINES%20ON%20THE%20MANAGEMENT%20OF%
+20APPLICATION%20FOR%20TRANSFER%20OF%20CREDIT%20AND%20C
+OURSE%20E XEMPTION.pdf
+
+
+## Examination Grading Scheme :: Official University Grades
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 301-301
+
+### Page 301
+EXAMINATION GRADING SCHEME
+The official University grades including the marks and their meaning are as follows:
+Marks Grade Grade Point Interpretation
+90.00 — 100.00 At 4.00 Distinction
+80.00 - 89.99 A 4.00 Distinction
+75.00 — 79.99 A- 3.70 Distinction
+70.00 — 74.99 B+ Good
+65.00 —- 69.99 B Good
+60.00 - 64.99 B- Good
+55.00 — 59.99 C+ 2.30 Pass
+50.00 — 54.99 Cc 2.00 Pass
+45.00 —- 49.99 C- 1.70 Fail
+40.00 —- 44.99 D+ 1.30 Fail
+35.00 - 39.99 D 1.00 Fail
+00.00 - 34.99 FE 0.00 Fail
+
+
+## Undergraduate Programme Goals and Learning Outcomes :: Bachelor of Computer Science (Computer System and Network)
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 202-204
+
+### Page 202
+PROGRAMME GOALS AND
+LEARNING OUTCOMES
+PROGRAMME GOALS
+To produce excellent graduates who are able to apply the knowledge and skills gained in the field
+of Computer Science and apply specific techniques to solve computer-based problems, as well as
+having entrepreneurship mindset.
+Programme Educational Objective:
+PROGRAMME LEARNING OUTCOMES
+At the end of the Bachelor of Computer Science (Computer System & Network) programme,
+graduates can:
+PO1
+Acquire a wider breadth of knowledge in computer science areas and a deeper
+understanding of Computer System & Network techniques.
+Apply an understanding of Computer Science domain to solve problems by exploring
+innovative practices for acquiring and analyzing information.
+Engage in practical solutions, which involves requirements gathering, designing, and
+developing algorithms and intelligence-based systems.
+Apply basic Mathematics and computer science theories specifically techniques in
+modelling and designing computer-based systems.
+Communicate effectively and engage in teamwork to solve issues related to
+intelligence-based computer science.
+Works effectively as individuals, and as a member of various technical teams.
+Initiate technical and/or societal innovation through technologies or entrepreneurship.
+Practice professionalism and ethics in executing tasks related to computing.
+PO2
+PO3
+PO4
+PO5
+PO6
+PO7
+PO8
+Graduates will demonstrate their ability to advance their careers in the computing profession, and
+will be engaged in learning, understanding, and applying new ideas and technologies as the field
+evolves (Professionalism).
+Graduates will have continuously advanced their knowledge, and improved competency in
+computer science to meet current and future needs (Continuous Personal Development).
+Graduates will contribute to sustainable development and the well-being of society through
+computer science practices (Societal Engagement).
+(1)
+(2)
+(3)
+
+### Page 203
+CURRICULUM STRUCTURE
+BACHELOR OF COMPUTER SCIENCE (COMPUTER SYSTEM AND NETWORK)
+‘ACADEMIC SESSION 2025/2026
+COURSE COMPONENT
+‘COURSE CODE UNIVERSITY COURSES: CREDITS SEMESTER:
+GIG1012_ Philosophy and Current Issues (for local student only)
+GLT 1049 Basic Malay Language (for international student) 2 2
+GIG1013, | Appreciation of Ethics and Civilizations 1
+COURSECODE | FACULTY CORE COURSES CREDITS | SEMESTER
+TF | Project Management 1
+consecon | SERS eeiasrmar | ercor_| soren
+Making the World a Better Place
+COURSE CODE PROGRAMME CORE COURSES CREDITS SEMESTER,
+WIA1006. Machine Leaming 3
+COURSE CODE SPECIALIZATION ELECTIVE COURSES (Choose 10:
+WiC2008. Internet of Things (#WIA1005) 3 tor
+‘WIC3001 ‘Mathematics in Networking 3 Tor?
+TOTAL CREDITS FOR GRADUATION 128
+# Prerequisite
+* Taken all Faculty and Programme Core Courses except Academic Project | and Academic Project I
+Pass all Faculty and Programme Core Courses except for Industrial Training and Academic Project I
+
+### Page 204
+‘COURSE PLANNING FOR BACHELOR OF COMPUTER SCIENCE (COMPUTER SYSTEM AND NETWORK)
+‘ACADEMIC SESSION 20252028
+‘GIGI012/ | Phiosophy and Curent ssios foo suet ony) Base
+estat) | Sac Enna a cLr1040 _| taay Language foreman tse 2
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+Wwixi0o1 —{ Comuing Napsmates | x ioo2 —| Dain Stuure @WOXIOT2
+nxico2 | Fundamentals of Prosranming = H FY
+woxi003 —[ Computer Systems and Orgnzaioy z wvs1005 —[ HetworkTochology Foundation x3
+wz001 | Thing and Communion Sts x wwi096 | Machine Learning z
+Taal} oar
+‘Semester | creas]
+“GiG1013 | Appreciation of Es and Cmlzstons z Co Curestum 2
+wxzo02 | Project Management eT Operaing Sstons z
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+WwiA2003—[ Probab and States 3 Spocaizaton Elocio 3) 3
+Win2006 —| Syston Anais and DosR x SpocazatonElecie 2)= EI
+WiAz008 —[ pavarced Hework Tettogy GRMATODS) n Spocalzaton Eleae (3)= z
+‘Dig! Desig and Hardware Descpton Language KIAR: Integy and Ants Corspon couree
+wx2n09 | Digit Deson and Hard a ‘eto aed Ant-Con 2
+Tae a
+Course Code | ‘Semester Semester? reais |
+| wnasoor P industil Tieng = 13002 | Aeademe Prowct 2
+Spooalzaton fiecie = 3
+Spooalzaton Elesie 5)" z
+Specalzaton Elec (6)= 3
+Spocatzaton Elec (7)™ z
+Unversty Eeciv (Custer: Tanking Matera Mnd& | >
+iiotect,
+Unwersty Elec (str 2: TochnategyAaical z
+| ittigsren ond Dota Anaties. Teche
+Tear] Tea |
+‘Course Code Semester Tre ‘Great Datrbaion
+Co Gureaan z ‘Course Component crea
+WSIS — acoso Pree MASOOD 5 Unversity Courses i
+Specialization Elecive () = 3 Faculy Gore Courses 7
+Specialization Bec (> el Trversy Seve Couses e
+Speaazaion Eecve 01™ z Programe Gore Courses a
+UniverstyElcive (Custer 3) Gaba lsvos and tasiod BatdialGarean
+Community Sustanabity Making the Worl Bat Pace |_* Seine oo 2
+Tear] ie "TOTAL CREDITS FOR GRADUATION |
+# Proroausi
+“Taken al Facuty and Programme Core Courses except Academic Project | and Academic Project I
+Pass all Facly and Programme Core Courses excop or Industral Tring and Acadomc Projoc I
+‘Spociaization Elective Courses wl be ofered on a rotation bass. Each Specialization Elective is schdued to un only once in evory academe session, thor in Somestr 1 of Somestor 2.
+
+
+## Undergraduate Programme Goals and Learning Outcomes :: Bachelor of Computer Science (Artificial Intelligence)
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 206-208
+
+### Page 206
+PROGRAMME GOALS AND
+LEARNING OUTCOMES
+PROGRAMME GOALS
+To produce excellent graduates who are able to apply the knowledge and skills gained in the field
+of Computer Science and apply specific Artificial Intelligence techniques to solve computer-based
+problems, as well as having entrepreneurship mindset.
+Programme Educational Objective:
+PROGRAMME LEARNING OUTCOMES
+At the end of the Bachelor of Computer Science (Artificial Intelligence) programme, graduates
+can:
+PO1
+Acquire a wider breadth of knowledge in computer science areas and a deeper
+understanding of Artificial Intelligence techniques.
+Apply an understanding of Artificial Intelligence domain to solve problems by
+exploring innovative practices for acquiring and analyzing information.
+Engage in practical solutions, which involves requirements gathering, designing, and
+developing algorithms and intelligence-based systems.
+Apply basic mathematics and computer science theories specifically Artificial
+Intelligence techniques in modelling and designing computer-based systems.
+Communicate effectively and engage in teamwork to solve issues related to
+intelligence-based computer science.
+Works effectively as individuals, and as a member of various technical teams.
+Initiate technical and/or societal innovation through technologies or entrepreneurship.
+Practice professionalism and ethics in executing tasks related to computing.
+PO2
+PO3
+PO4
+PO5
+PO6
+PO7
+PO8
+Graduates will demonstrate their ability to advance their careers in the computing profession, and
+will be engaged in learning, understanding, and applying new ideas and technologies as the
+Artificial Intelligence field evolves (Professionalism).
+Graduates will have continuously advanced their knowledge, and improved competency in
+computer science and Artificial Intelligence to meet current and future needs (Continuous Personal
+Development).
+Graduates will contribute to sustainable development and the well-being of society through
+computer science and Artificial Intelligence (Societal Engagement).
+(1)
+(2)
+(3)
+
+### Page 207
+CURRICULUM STRUCTURE
+BACHELOR OF COMPUTER SCIENCE (ARTIFICIAL INTELLIGENCE)
+ACADEMIC SESSION 2025/2026
+‘COURSE COMPONENT
+COURSE CODE UNIVERSITY COURSES GREDITS
+‘cicioz Phiosophy and Curent issu student
+GLT1049) Malay Language Communication (fer intemational studend 2
+‘GiGi013 ‘Appreciation of Ethics and Guvitzations 2
+'G1G1003 Basic Entrepreneurship Culture 2
+GLOOOC English or Communication (1) 2
+(GLb900C Engis for Communication (2) 2
+‘Go-Gurneuium (1) 2
+Co-Cumeuium 2 2
+Toial 14
+COURSE ‘CRED
+fee FACULTY CORE COURSES A
+Wixt0oT ‘Computing Mathematics 3
+wiixs002 Fundamentals of Programming
+| -“woxtoos |" Computer Systems and Omanczation 2
+Wx2008 Thicking end Communication Skil :
+wixz002 Project Management 3
+Total 17
+CODE ‘
+University Elecive (Cluster 1) - Thinking Mattrs. Mand & Inelect 2
+Unwvarsiy Elecive (Clistor2)~Technobegy/Anifcal intelligence and Data 3 A
+Andivis: Techie
+University Elecive (Guster 3- Global Isues.and Community 2 rn
+ustamnabilty Making the Word 9 Boter Pi
+KIAR: Intogrty and Ant Corruption course 2 2
+COURSE ‘CRED
+R
+WIAi002 Data Structure (WIX1002) 3 2
+WwiAr003 ‘Computer Systom Achtectore GUXTOOS) 3 z
+WIAT005, Tetwork Technology Foundation rn 2
+WIA1006- Machine Leaming. 2b 2
+WIAi007 Inioduction to Data Sones 3 +
+wiazoot Database 3 2
+Wiazo03 Probabity and Statistics 3 3
+WiA2004 ‘Operating Systems 4 4
+WA2005 Algorithm Design and Analysis @WWATOO2) 4 4
+WiA2006 siom Analysis and Design 3 3
+WiA2007 ‘Mobile Appication Development 4 3
+WHA3004 Ingustal Taig * 12 3
+WiA3002 Academe Project = 3 a
+WHA3003 Academe Project I NIASOOD) 3 7
+Toial 39
+Gee ‘SPECIALIZATION ELECTIVE COURSES (Choose only 10 courses)
+WIG2005 Internet of Things (AWIATO05) 3 4
+wioz001 Knowledge Representation and Reasonng 3 4
+wibz002 ‘Compuing Mathematics z 4
+Wid2003 ‘Cognitive Science 3 4
+WiD3001 Functional nd Logis Programming 3 7
+Wi3002 Tatura Language Processing z a
+“wi03007 Fuzzy Lois (aWixi001) 3 Z
+win3010 ‘Aulonomous Robots 3 S
+WID3014 Deep Leaming zl -
+wi3012 Evolutionary Computation 3 z
+‘wins013 ‘Computer Vision and Pater Recoaniion 2 a
+wi3014 Practical Anica! iteliganc 3 z
+Wi03015 Humoncal Analysis 3 7
+wigso04 Virtual Realty FY 6
+Total 30
+"TOTAL GREDITS FOR GRADUATION 728
+# Prerequisite
+* Taken all Faculty and Programme Core Courses except Academic Project | and Academic Project I
+"Pass all Faculty and Programme Core Courses except for Industral Training and Academic Project I
+
+### Page 208
+‘COURSE PLANNING FOR BACHELOR OF COMPUTER SCIENCE (ARTIFICIAL INTELLIGENCE)
+"ACADEMIC SESSION 2026/2026
+Tave | Course Course
+f ay ‘Semester 1 Credite a ‘Semester? recite
+7 i Erie icto12/ | Pritosophy and Curent Issues (ora! ste ety) /
+creme | ase naaaetinetrati Cuma) a ‘GLT1040 | Malay Language Communication (rateratona student) | 2
+"SCHOO |“ Eraish for Communication z "StT00o | “Enaish for Communication 2) 1
+Wwixt001 | Computing Mathomates | 3 "wA1002 —| Data Siucure awc1002) 3
+Wwix1002 | Fundementas of Progamming 5 Wia1003 | Computer Swsiom Avchtocure WKTOOS) 3
+Wix1003 | Computer Systems and Organization 3 "WIAt005 —[~ Network Technology Foundation 4
+\watoo7 —| induction te Dat 3 "wiA1005 —[ Machine Lear 3
+Taial_[ 8 Teal is
+‘Course Course
+A 2
+—_ ‘Semester Credits oe ‘Semestr Creaits
+GIG1013 | Appreciation of Eics and Civizaton Co-Goanouum (0
+wo7001 | Thinkag and Communication Stas 2 TWHADOGA | Operaung Systems 4
+wxz002 | Project Management 3 WiA7005 [Algorithm Design and Analysis IATOOD) 4
+‘wiazoo1 [Database 3 Specalzaton Eiecwe() 3
+WiAz003 | —Probebany and Stasis 3 Specalzaton Ewe 2) 3
+Waz006—|~Systom Analyss and Desi 3 Spocalzaton Eeawe3) 3
+WIA7007 —| Mobile Agplcation Development 4 University Elective (Custer 2
+Teiat_[ 77 Total 7
+‘course Course
+‘Semester Credits ��Semester? Crete
+Code, Code
+WiAs001 | Indus rong Z "WiAS002 | Acogemic Pros = 3
+Specalzaton Etecwoy 3
+Spocalzaton Ewawe @) 3
+Specialzaton Eecve @) 3
+Soeciizaion Ede
+Univorsty oct (Guster 2.
+Unversty leche (Custer 3)
+etal | az etal 79
+‘Couree Cred
+sole ‘Semester 1 a “Creait Distribution
+Co-Curiouum (2) 2 ‘Course Component Create
+THIABOOS | Acadomic Prowet I (AWASOOD) 3 Univorsty Cou 14
+‘Spocalzaton Exctve (6) 3 Faculy Cow Courses ar
+ectve (9) 3 worst Elesve Courses
+‘Spocalzaton Eictvo (10) 3 Programnmo Core Courses. 30
+‘University Elective (Custer 3): Global Issues and
+Communty Sustainaity: Making tho World a Bettor 2 Universty Courses “
+Proce
+Teter | "TOTAL CREDITS FOR GRADUATION [125
+# Prerequisite
+Taken al Facuty and Programme Core Courses except Academic Project | and Academic Project
+Pass all Faculty and Programme Core Courses excopt fr indusinal Tring and Academic Proje I
+‘Spocaization Elective Courses wil be offered ona rotation bass. Each Specialization Elactve is scheduled lo run only once in every academic session, ether in Semester 1 or Somestor 2.
+
+
+## Undergraduate Programme Goals and Learning Outcomes :: Bachelor of Computer Science (Information Systems)
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 210-212
+
+### Page 210
+PROGRAMME GOALS AND
+LEARNING OUTCOMES
+PROGRAMME GOALS
+To produce excellent graduates who are able to apply the knowledge and skills gained in the field
+of Computer Science and apply specific Information Systems techniques to solve computer-based
+problems, as well as having an entrepreneurship mindset.
+Programme Educational Objective:
+PROGRAMME LEARNING OUTCOMES
+At the end of the Bachelor of Computer Science (Information Systems) programme, graduates
+can:
+PO1
+Acquire a wider breadth of knowledge in computer science areas and a deeper
+understanding of Information Systems techniques.
+Apply an understanding of Information Systems domain to solve problems by
+exploring innovative practices for acquiring and analyzing information.
+Engage in practical solutions, which involves requirements gathering, designing, and
+developing algorithms and intelligence-based systems.
+Apply basic mathematics and computer science theories specifically Information
+Systems techniques in modelling and designing computer-based systems.
+Communicate effectively and engage in teamwork to solve issues related to
+intelligence-based computer science.
+Works effectively as individuals, and as a member of various technical teams.
+Initiate technical and/or societal innovation through technologies or entrepreneurship.
+Practice professionalism and ethics in executing tasks related to computing.
+PO2
+PO3
+PO4
+PO5
+PO6
+PO7
+PO8
+Graduates will demonstrate their ability to advance their careers in the computing profession, and
+will be engaged in learning, understanding, and applying new ideas and technologies as the
+Information Systems field evolves (Professionalism).
+Graduates will have continuously advanced their knowledge, and improved competency in
+computer science and Information Systems to meet current and future needs (Continuous Personal
+Development).
+Graduates will contribute to sustainable development and the well-being of society through
+computer science and Information Systems practices (Societal Engagement).
+(1)
+(2)
+(3)
+
+### Page 211
+CURRICULUM STRUCTURE
+BACHELOR OF COMPUTER SCIENCE (INFORMATION SYSTEMS)
+‘ACADEMIC SESSION 2025/2026
+‘COURSE COMPONENT
+COURSE CODE
+GiGi012 Philosophy and Current ssves (for local student ont
+‘BLT 1049. ‘Malay Language Communication (fer infemational student) 2 2
+GiG1013, ‘Appreciation of Ethics and Grvzatons 2 7
+‘G1G1003 Basic Entrepreneurship Culture 2 1
+‘GLDOOK, English for Communication (1) 2 1
+(GLDOOK. English for Communication 2) 2
+‘Co-Curneuim (1) 2 2
+‘Co-Curiculum (1) 2 fl
+Tota | 14
+COURSE CODE FACULTY CORE COURSES CREDITS.
+Wixtoo1 ‘Computing Mathemabes | 3 1
+wixt002 Fundamentals of Progremang, 5 i
+Wwixt003 ‘Computer Systems and Organizaion 3 1
+wx2001 “Thinking end Communication Skis 3 1
+|___WIx2002_ | Project Management 3 4
+Universiy Elecive (Custer 1)= Thinking Matters Mind & intelect 2
+University Elecive (Cluster 2)~ Technology/ArticalInteligence and Data 5
+Analvties:i-Techie
+University Elective (Cluster 3- Global Issues and Communily Sustanabiiy. iz 4
+Making the World a Better Pace
+'KIAR: integrity and Anti-Corruption course 2 2
+Total n
+COURSE CODE PROGRAMME CORE COURSES. CREDITS | SEMESTER.
+WIATOO! information Systems 3 7
+WiAToo2 Data Structure (#WDcTO02) 3 2
+WIATOO3 ‘Computer System Architecture (AMDCIOOS) 3 z
+WIAt005 Network Technology Foundation 4
+WIAt006. Machine Leeming 3 2
+Wiazoo1 Delabaso 3 4
+| ——wiaz00s | Probabitty and Stasis 3 1
+WIA2004_ Operating Systems 4
+WiA2005 ‘Algonthm Design ond Analysis GUMATOOD) 4 2
+TWiA2006. System Analysis and Design 2 4
+‘Wiagoor- Mobile Appication Development 4 1
+Wias0o1 Industial Trainng* 2 +
+Twias0o2 ‘Academic Project = 3 2
+WIA300 ‘Acodemic Project I (AIAZOO2) 5 fl
+Tota | 59,
+COURSE CODE SPECIALIZATION ELECTIVE COURSES (Choose only 70 courses) CREDITS | SEMESTER.
+Twic2008 Tafernet of Things 3 Tor?
+WiEZ001 “Trends in information Systems. = Tor
+Wie 2002 “Open-Source Programming. Appication and Technolog) fe 00?)
+NE2003. introduction to Data Science 3 tor
+WIEZ005, Information Retrieval and Web Search 3 Lor
+WiE3001 ‘Advanced Database 3 or?)
+WIE3002, Elecvonic Commerce a Lor?)
+WIE3003 Information System Contol and Securh 3 Loc?)
+WIE3005; Knowledge Management and Engineering 3 Tor?)
+TWE3005 Information System Auciting 3 Tor?)
+WiE3007 Data Mining and Warehousing 3 Lor?)
+WIE3010 Data Visualization 3 Tor?)
+WiE3012 ‘Business Analyies and Inligence 3 Tor?
+WiF2003 Wleb Programming 3 Tor?
+Totat | 30,
+"TOTAL CREDITS FOR GRADUATION | 128
+# Prerequisite,
+Taken all Faculty and Programme Core Courses except Academic Project | and Academic Project I
+Pass all Faculty and Programme Core Courses except for Industrial Training and Academic Project I
+® Each Specialization Elective Course is only offered ONCE every academic session, either on Semester 1 OR Semester 2.
+
+### Page 212
+‘COURSE PLANNING FOR BACHELOR OF COMPUTER SCIENCE (INFORMATION SYSTEMS)
+‘ACADEMIC SESSION 2025/2028
+Level | Course Code, ‘Semester? ‘Greats | | Course Code ‘Semester? ‘creas
+icEirepreneut re ‘61G1012/ | Philosophy and Curent issues focal student on |
+S210 | Deere te 2 GLT1040._| Malay Language Communication (intemationa stdert ss
+SEDO _| Eras for Communion z ‘GLDOO [Engi or Communion (2) z
+nX3001 —| Computing Mathematics | 3 WA1002 —[ Data Stucture (#N1X1002) =
+1 [wx1002—[ Fundementas of Programming 5 WiA1003—[ Computer Systom Archtecture (ANAXTOOS) 3
+WIX1003 | Computer Systoms and Organizaion 3 WA1005—[-Hotwork Technology Foundation 4
+WIA100; [Infomation Systoms E: TWint005 —| Machine Learang EI
+Tot [aa Total | a8
+‘Semester ‘creas |
+'GiG1013 | Agpreciaion of Ethie and Cusizatons 2 2
+‘wx2o01 | Thinking and Communication Skis EI TWHAROOR 7
+| wrx2002 —[Proes Menanement 3] [-wnazoos I cs
+{waz001 [Database EI EI
+2 [Liwio0s —[ Probabany ana Saat E: =
+"WiA2006—| System Analysis and Desig EI z
+"wiA2007 | Mebile Application Develooment 4 KIAR: Ifegry and Ard Coription course 2
+cr Teta |
+‘Semesiery | Greats | | Course Gage [semester creits|
+‘wias0o1 | industiel Tanna o wiasoo2 | Academe Project =
+Specalzaten Elev @)= EI
+Speciatzaton Elecive @)™ EI
+Speciatzaton Eleavo 6) z
+Specatzaten Eleaive (7) =
+‘University Elective (Clustor 1): Thinking Matto: Mind & a
+3 nttct
+Uniorsfy Elecive (Custer 2): Technclogy/Arical 2
+Inieligonce and Data Anais Toche
+Total | 72, C etal [78
+course Cage [ ‘Semester credits |
+Co-Crcutum 2) [create |
+| winso03 Academic Prowct I caMmAGO0a ra [Unversity Courses 14
+‘Spocelzaton Elective 8)" z Focully Core Courses ar
+4 Specielzation Elective (2)™ = Unversity Elective 8
+‘Speciation Electve 10)" Fl [Programme Core Cou: a
+Universty Elective (Clustor 3): Global issues and Jntzaton Elective Courses
+‘Communty Sustanobitty Making be World Better Pace |_? Sepia S iad
+Total | 7 "TOTAL CREDITS FOR GRADUATION | 128]
+# Provequsito
++ Takon al Faculty and Programme Core Courses excapt Academic Project | and Academic Project
+Pass all Faculty and Programme Core Courses except for industtal Training and Academic Project I
+‘Specialization Elective Courses wll bo cffored on a rotation basis. Each Specialization Elective fs Scheduled to run only once in every academic session, thar in Semestr 1 or Semester 2
+
+
+## Undergraduate Programme Goals and Learning Outcomes :: Bachelor of Computer Science (Software Engineering)
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 214-216
+
+### Page 214
+PROGRAMME GOALS AND
+LEARNING OUTCOMES
+PROGRAMME GOALS
+To produce excellent graduates who are able to apply the knowledge and skills gained in the field
+of Computer Science and apply specific techniques to solve computer-based problems, as well as
+having an entrepreneurship mindset.
+Programme Educational Objective:
+PROGRAMME LEARNING OUTCOMES
+At the end of the Bachelor of Computer Science (Software Engineering) programme,
+graduates can:
+PO1
+Acquire a wider breadth of knowledge in computer science areas and a deeper
+understanding of Software Engineering techniques.
+Apply an understanding of Software Engineering domain to solve problems by
+exploring innovative practices for acquiring and analyzing information.
+Engage in requirements gathering, designing, implementing, and evaluating
+software or IT-related systems.
+Attain an ability to apply mathematical skills and/or toolset in the software
+development life cycle.
+Communicate effectively and engage in teamwork to solve software related
+problems.
+Function effectively as individuals, and as a member of diverse technical teams.
+Initiate technical and/or societal innovation through technologies or entrepreneurship.
+Practicing high ethics in the computer science profession, especially when it comes
+to computer systems, organizations, and society.
+PO2
+PO3
+PO4
+PO5
+PO6
+PO7
+PO8
+Graduates will demonstrate their ability to advance their careers in the computing profession, and
+will be engaged in learning, understanding, and applying new ideas and technologies as the
+Software Engineering field evolves (Professionalism).
+Graduates will have continuously advanced their knowledge, and improved competency in
+computer science, software development and related technologies to meet current and future
+needs (Continuous Personal Development).
+Graduates will contribute to sustainable development and the well-being of society through
+professional practices (Societal Engagement).
+(1)
+(2)
+(3)
+
+### Page 215
+‘CURRICULUM STRUCTURE
+BACHELOR OF COMPUTER SCIENCE (SOFTWARE ENGINEERING)
+ACADEMIC SESSION 2025/2026
+‘COURSE COMPONENT
+COURSE CODE “UNIVERSITY COURSES crepits | SEMESTER
+GIG1012 Philosophy and Current Issues (for /ocal student only)
+GLT1049. ‘Malay Language Communication (for intemational student) 2 2
+(GiG1013 ‘Appreciation of Ethics and Gvilzations 2 7
+GIG1003. Basic Enirepreneurship Culture 2 1
+[LOOK Enalsh for Communication (1) 2 1
+LDOOK, English for Communication 2) 2 2
+[Co-Curiculum (1) 2 2
+‘Co-Curricutum 2) 2 ‘1
+Tota | 14
+‘COURSE CODE FACULTY CORE ‘CREDITS,
+wixt001 ‘Computing Mathematics | 3 1
+Wwix1002, Fundamentals of Programming 5 1
+Twixt003 ‘Computer Systoms and Organization 3 1
+wix2001 Thinking and Communication Skis 3 +
+wix7002 Project Management 3 +
+Teta | 17,
+EXTERNAL UNIVERSITY ELECTIVE COURSES
+COURSE cone! STUDENT HOLISTIC EMPOWERMENT (SHE) (eats || Eo ee
+Universi Elective (Cluster 1) = Thinking Matters: Mind & Intellect 2
+University Elective (Cluster2) - Technology/AriftalIntoligence and Data = 3
+Analytics: i Tectio.
+University Elective (Cluster 3) - Global Issues and Community Sustainability: 1
+Making the Weld a Better Place
+"KIAR: Integnity and Anti-Corruption Ouse Zz
+Is 8
+PROGRAMME CORE COURSES: | SEMESTER |
+WiA1002, Data Structure (aWIX1002) 5
+WIA1003, ‘Computer System Archtecture (@WIXT003) 3
+WIA1005, Network Technology Foundation 4 2
+WIA1006, Machine Learning 3 2
+WiA2001 Database FI 1
+WIA2002, Software Modeting 3 1
+WiA200%. Probabilfy and StoiStES 3 1
+‘WiA2004 ‘Operating Systems. 4 2
+WIA2005, ‘Agonithm Design and Analysis (AWATOO2) 4 2
+TWiazoor- Mobile Application Development 4 fl
+WiA2010 Human Computer Interaction 53 +
+WiA300t Indusval Training 2 1
+TWiAs0o2 ‘Academic Project = 3 2
+WIA3008. ‘Academic Project IT GWIASOO2) 5 i
+Tota | 39
+‘COURSE CODE "SPECIALIZATION ELECTIVE COURSES (Choose only 70 courses) | CREDITS
+WiEZ002 Sofware Requirements Engineering 3 or?
+WIEZ003. ‘Web Programming 3 “Lor?
+WiF3001 Software Testing 3 Tor?
+WIF3002 ‘Software Process and Quali {3 Tor?
+WIE3004 Software Architeclure and Design Paradigms (AWIAZ002) 3 “Lor?
+WIE3005, Software Maintenance and Evolution 3 Tor?)
+WiE3006. ‘Component Based Software Engineering (@WIA2002) [3 or?
+WiE3008: Real Time Systems. 3 or?
+WIE3009. Python for Scientific Computing 3 Tor?)
+WiE3010 Programming Language Paradigm 3 “Lor?
+WIESoTT ‘Concurrent and Parallel Proaramming (@WIX1002) (RWIAZ004) 3 Lor?
+WiG3005 ‘Game Development 3 Tor?
+Wic2006- Internet of Things @VWATOOS) 3 or?
+Total | 30
+TOTAL CREDITS FOR GRADUATION | 128
+# Prerequisite
+‘Taken all Faculty and Programme Core Courses except Academic Project | and Academic Project I
+** Pass all Faculty and Programme Core Courses except for Industrial Training and Academic Project I
+© Each Specialization Elective Course is only offered ONCE every academic session, either on Semester 1 OR Semester 2.
+
+### Page 216
+‘COURSE PLANNING FOR BACHELOR OF SOFTWARE ENGINEERING
+"ACADEMIC SESSION 20252028
+[Revel | Course Code [Semester
+{GIO12/ | Phiosophy and Curent ses (roca student oni)
+Se 2 Giiiow | Kner arauao Conmuncatontor ntanatnal siden) | 2
+Enaish for Communication (1) 2 } English for Communscation (2)
+Wixioor —| coming Mahemates | s Wia 002 —[ Data Stucke GRNXI002) =
+1 [Peitacooa Trtmentats of Progaming = Wh 003 — | Compute Syste Artec (ANETOOO) =
+1003 —| Congutes Systems and Oren aon Wwat0os —[ Hetwor Teology Foundation r
+yn2o10 | Hunan Conga ira EI waioos —[ Mache earn
+Tea = Tata rn
+‘Semester [Feourse Code [Semester Treats |
+GIGTO1S | Aggrocaton of Ees and Crvzatons 2 o-Garncaum 2
+Wwix2001 | Tanking and Communication Sis = WOOT — | Operating Systems r
+wixz002 | Pret Wanagement FI WiA2005 —[ Agari Dssen and Ani (AMATO) ry
+Wiazoot —| Dalsace z1 Spocsleaion oes 1)" 3
+Wwia2002 —| Sofware tng > ‘Specaliabon Elecbve 2) =
+$ WiA2003 | Probability and Statistics 3 ‘Spocializabon Elective (3) = EI
+WA2007 —| Nobile Appteaton Development n TIAR Integr and Ant Corgan oa 2
+Total Fa Taal Fa
+Course Code Semester Greats | |Tcourse cose Semeer? Crea
+WiAxor | indus rang 2 WiAs002 | Asadomis Poppa 3
+$pecializaton Elective (4) 2
+Specialization Elective (5)~
+[Seocaizaton Locto (6)=
+Soecalzaton Elect (= rT
+fi UnwvoratyElecve (Cluster 1 Thing Matis Me & :
+briotet
+Unwersty Elec (Chater 2) TecinohaAihaar 7
+intgancs and Daa Anayics Teche.
+Tear = or 7s
+Course Code Semester 1 Credit Distribution |
+Co-Gumeum 2 2 ‘Coue Component Create
+SCT 5 [om it
+Speciation Elective 8) = Fac Core Cours 7
+Specialization Elective 9) zy Unneraty Ect Cou n
+4 Specialization Elective (10) *_ 3 | Prooramme Core Courses 2
+Unveraty Echo (Custer 9; Global eves and 2 ‘SpecelaatonElectve Courses * 20
+Tear = "TOTAL CREDITS FOR GRADUATION. 7
+Prorequiste
+“Taken al Fecuty and Programme Core Courses excopt Academic Project | and Academic Project I
+Pass all Facalty and Programme Core Courses excep er Indust Training and Academic Projoc I
+‘Specialization Bc Courses willbe offered on a rolaton bass Each Specialzalion lace ts scheduled fo run cry once every academic session, ether n Semester 1 or Semester 2.
+
+
+## Undergraduate Programme Goals and Learning Outcomes :: Bachelor of Computer Science (Multimedia Computing)
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 218-220
+
+### Page 218
+PROGRAMME GOALS AND
+LEARNING OUTCOMES
+PROGRAMME GOALS
+To produce excellent graduates who are able to apply the knowledge and skills gained in the field
+of Computer Science and apply specific techniques to solve computer-based problems, as well as
+having an entrepreneurship mindset.
+Programme Educational Objective:
+PROGRAMME LEARNING OUTCOMES
+At the end of the Bachelor of Computer Science (Multimedia Computing) programme,
+graduates can:
+PO1
+Acquire a wider breadth of knowledge in computer science areas and a deeper
+understanding of Multimedia Computing techniques.
+Apply an understanding of Computer Science domain to solve problems by exploring
+innovative practices for acquiring and analyzing information.
+Engage in practical solutions, which involves requirements gathering, designing, and
+developing algorithms and intelligence-based systems.
+Apply basic Mathematics and computer science theories specifically techniques in
+modelling and designing computer-based systems.
+Communicate effectively and engage in a teamwork to solve issues related to
+intelligence-based computer science.
+Works effectively as individuals, and as a member of various technical teams.
+Initiate technical and/or societal innovation through technologies or entrepreneurship.
+Practice professionalism and ethics in executing tasks related to computing.
+PO2
+PO3
+PO4
+PO5
+PO6
+PO7
+PO8
+Graduates will demonstrate their ability to advance their careers in the computing profession, and
+will be engaged in learning, understanding, and applying new ideas and technologies along with the
+evolution of the field of Multimedia Computing (Professionalism).
+Graduates will have continuously advanced their knowledge, and improved competency in
+computer science and Multimedia Computing to meet current and future needs (Continuous
+Personal Development).
+Graduates will contribute to sustainable development and the well-being of society through the
+practices of computer science and Multimedia Computing (Societal Engagement).
+(1)
+(2)
+(3)
+
+### Page 219
+CURRICULUM STRUCTURE
+BACHELOR OF COMPUTER SCIENCE (MULTIMEDIA COMPUTING)
+‘ACADEMIC SESSION 2025/2026
+‘COURSE COMPONENT.
+‘COURSE CODE Si esea OU creoits | SEMESTER
+GIG1012 Phiosophy and Current Issues (for local student only)
+GLT1049 Basic Malay Language (for infemational student) a 2
+GIGI013 ‘Appreciation of Ethics and Civilizations 2 7
+‘GIG1003 Basic Entrepreneurship Culture 2 1
+GLDOOK Enaiish for Communication 1) 4
+GLDOXX English for Communication 2) 2 2
+(Co-Curriculum (1), 2 2
+(Co-Curmculum 2) 2 1
+Total 14
+‘COURSE CODE, FACULTY CORE COURSES CREDITS | SEMESTER
+WIX1001 ‘Computing Mathematics | 3 1
+Wix1002, Fundamentals of Programming 5 1
+Wix1003 ‘Computer Systems and Organization. 3 1
+Wix2001 Thinking and Communication Skils, 3 1
+wix2002 Project Management 3 1
+Total a7
+EXTERNAL UNIVERSITY ELECTIVE COURSES
+RISE OVE! ‘STUDENT HOLISTIC EMPOWERMENT (SHE) ESTE | [SEMESTER
+‘University Elective (Gluster 1)- Thinking Matters: Mnd & intellect
+University Elective (Cluster 2) Technology/Artiical inteligence and Data
+Analytics: Techie
+University Elective (Cluster 3 - Global Issues and Community Sustainability. 2 i
+Making the World a Better Place
+KIAR: Integrity and Anti-Corruption course. 2 2
+Total 3
+(COURSE CODE, PROGRAMME CORE COURSES: ‘CREDITS:
+Wiat002 Data Structure (AWIX1002) $
+WIA1003 ‘Computer Systom Architecture GAWIX1003) 3
+WIA 100 Network Technology Foundation 4
+WiA1006 Machine Leaming a
+WiA1008 Fundamental of Multimedia 3
+WiA2001 Database 3
+WiA2003, Probabilly and Stalistics 3
+WiA2004 ‘Operating Systems. 4
+WIA2005 ‘Aigonithm Design and Analysis (AWATOO2) 4
+WIA2006 ‘System Analysis and Design 3
+WIA2007 Mobile Application Development 4
+WiA3001 Industrial Training * az
+WiA3002 ‘Academic Project 3
+WiA3003, ‘Academic Project I @WIAIO02) 5
+Total 59
+(COURSE CODE, ‘SPECIALIZATION ELECTIVE COURSES (Choose only 10courses) | CREDITS | SEMESTER
+WiG2001 Diaital image Processing 2 atau 2.
+wiG2002 ‘Computer Graphics 3 atau 2
+wiG2004 Audio Synthesis. 2 atau 2
+WiG200 Interactive Design 3 “atau
+WIG3001 Mathematics for Multimedia B atau 2
+WiG3002 Rendering and Animation 3 “atau 2
+WIG3003 Multimedia Programming 3 atau 2
+WIG3004 ‘Virtual Reality 3 atau 2
+WIG3005 ‘Game Development 3 atau 2
+WIG3006. Digital Video Processing 3 ‘Letau 2
+WIG3007 ‘Special Topics in Multimedia 3 “atau 2
+WIG3008 ‘Mulimedia Forensic and Secariy 3 atau 2
+WIE3010, Data Visualization 3 atau 2
+WiF2003 ‘Web Programming 3 Tetau 2
+Total 30
+TOTAL CREDITS FOR GRADUATION | 128
+# Prerequisite
+* Taken all Faculty and Programme Core Courses except Academic Project | and Academie Project I
+Pass all Faculty and Programme Core Courses except for Industrial Training and Academic Project I
+
+### Page 220
+‘COURSE PLANNING FOR BACHELOR OF COMPUTER SCIENCE (MULTIMEDIA COMPUTING)
+"ACADEMIC SESSION 2025/2026
+[Revel | Course Code | "Semester credits | ourse Code |
+crciom | Bese enteprenausie Cute ‘xct012/ | Pesorhy and Gaent ses tr tent ri Bask
+tia . GLT1049 Malay Language (for intenatonal student)
+‘SCHOO _| Engin for Communication ‘GLOOX | Engish for Communtcaton (2
+Wwix1001 | Compusng Matberatcs L "WA1002 —[ ata Stucisre UNVIXIO2)
+1 [iinct0o2 [Fundamentals of Programing. TWA1003_—| Computer System Archaocture (ADETOOS)
+Wix1003 [Computer Systems and Organzaton TWA1005 | Network Technology Founsate
+WiA008 —| Fundamental of Multimedia Wiat006 | Machine Learning
+Total | 8
+‘Semester
+“<iGi013 | Apprecaton of Ethics and Guiizalons
+| Course Code | Semester2 Treats |
+‘Co-Cumiesm i
+Wwixz001 | Thnlang ane Communication Sls TWHATOGE_| Operating systems
+Wix7002 | Provect Management 1WAZ005 | Aljntim Design and Anais (@NTATOOD
+Wwiaz0ot —| Database.
+Wia2003 —| Probabaty and Satan ‘Specalzaton Elective 2)"
+2 | wir200e [System Aneiyss and Design ‘Spoctatzaton Elocive 3)"
+q
+r
+rn
+‘Spocelzaton Elecivo (1) = x
+z
+Wwiaz007 | Mobi Appcation Development KAR: Infegrty and Ants Cornapton course
+z
+EI
+rT
+EI
+x
+a
+{course Code ‘Semester | course code |
+WASG01 —[industiel Trang "143002 — | Academe: Prowet = 3
+‘Specalzaton Elecivo 5) FI
+‘Specialization Elective 6) FI
+‘Specialzaton Elective (7) Fl
+5 University Elective (Cluster 1); Thinking Matis: Mind & 4
+Intec
+‘Univraty Elective (Cluster 2) Technelogy/Arfical =
+Lnteigence and Data Anais: Tene
+Tota | Tota | as
+Course Code. Semester relia ‘edi Distibution
+Co-Curiculam 2) 2 [Course Component reais
+TASES | Academic Prose I GAWASOOD = ‘Unversity Courses. 14
+Specaizaton Fete 8) = Faculy Core Courses rT
+Spocalzation Ewctve (9) 3 Unversity Erectve Couses 3
+‘ Specialization Elecve (17> x Programme Core Courses Ed
+University Elective (Cluster 3) Global asues and ean Eset Coueses
+(Communty Susianatinty: Making te World Boter Pico |__* sir aah =
+Tota] 6 "TOTAL CREDITS FOR GRADUATION | 728
+Pre-requsite
+Taken al Facuty and Programme Core Courses except Academic Project and Academic Projet I
+Pass all Faculy and Programme Core Courses excop or indusinal Training and Academic Project I
+‘Specialization Elecive Courses willbe offered ona rotaton basis. Each Specalzaton Electives scheduled to run only once in every academic session, thorn Semester 1 or Semestr 2
+
+
+## Undergraduate Programme Goals and Learning Outcomes :: Bachelor of Computer Science (Data Science)
+
+- scope_label: undergraduate
+- source_doc: Complete Handbook
+- pages: 222-224
+
+### Page 222
+PROGRAMME GOALS AND
+LEARNING OUTCOMES
+PROGRAMME GOALS
+To produce excellent graduates who can apply the knowledge gained in the field of Data Science
+and apply scientific techniques to solve computer-based problems as well as having
+entrepreneurship mindset.
+Programme Educational Objective:
+PROGRAMME LEARNING OUTCOMES
+At the end of the Bachelor of Computer Science (Data Science) programme, graduates can:
+PO1
+Gain strong knowledge in Data Science and across Computer Science field.
+Engage in practical training that involves collecting, cleaning, and exploring data to
+extract information and gain insights from the data.
+Demonstrate social skills and responsibility to the community using the knowledge
+and skills acquired throughout the Data Science pipeline.
+Apply high ethical values in professional practice especially in dealing with data,
+organizations, and society.
+Communicate effectively and demonstrate specific skills involved in communicating
+data, whether verbal or visual.
+Apply data science concepts and methods to solve problems in a real-world context
+with effective data-driven solutions.
+Use lifelong information management and learning skills to acquire knowledge and
+skills in Data Science.
+Identify and analyze business opportunities and can develop a new Data Science
+related business plan.
+PO2
+PO3
+PO4
+PO5
+PO6
+PO7
+PO8
+Graduates can conduct data-driven investigations by accessing, evaluating, and analyzing
+data sets to obtain useful information; competent in the use of appropriate tools and
+technologies in building data models capable of making predictions and solving problems
+involving different set of data from any domain and developing data products.
+
+### Page 223
+CURRICULUM STRUCTURE
+BACHELOR OF COMPUTER SCIENCE (DATA SCIENCE)
+"ACADEMIC SESSION 2uzst020
+COURSE CODE
+Sawa gunie Basic Malay Language (for international student)
+EGTOTE [Ares of Eicon Grito
+‘GG 1003 | Baste Enroprnous
+‘GG Toot ——[itrmation Lerey
+‘161008 [Soa Enoagemet
+TEETHOOR [Eni for Commancaon
+EDGR | Engi or Commuaon 2)
+o-Curivcalun
+Eiema Facity Eaves
+COURSECODE FACULTY CORE COURSES
+Woxt0o1 | Computing Nahemats
+WoxtaG2 | Fundamentals of Presramning
+WORt005 | Computer System and Organization
+Woez261 | Tirkng end Communication Sls
+Woxaina ——[ Preect Management
+COURSE CODE, PROGRAMME CORE COURSES
+W703 | roduiontoData Soeres
+WATOOH ——[ ntermaton Systems
+Ware? —[ bats Siacire
+Wirt ——[ Computer Syston Achiooure
+WiAT005 ——[ NetvonTecinoogy Foundation
+WiAzior | Daiabase
+Wikzi02 ——| Sofware og
+WiAza03 | Probably and SiaCs
+Wikzto4 ——[ Operating Systoms
+Wwid2t08——[ Machine eamna
+‘iz300s | Proessona DevelopnooF
+W006 ——| Data Sanco and ArBCanOT
+Wt3007 ——[ industrial Soliton Dowtomor
+Wii2007 | Dela Sues Prosar”
+Wino? ——| Date Sus aus TERT
+COURSE CODE, FACULTY ELECTIVE COURSES [Choose on COUR]
+Woo! | Sof Campana
+Woesao [Socal nema
+Wat —[ ntrmeton Socurly Manager and ETS
+Wiczt6¢ —— [irene Technaiany
+Witao1 | Data anayios
+Wid ——[Knonfedge Represartaton and Reasoning
+wibzi02 ——[ Comping Mathers
+‘Wid300] | Funona and enc Programming
+Wwidsto2 | Naural Language Processing
+WIESIO7 [Dat Wig ad Worenousing
+WESITO——[ bata Vstzaton
+Wieapig | Business Anaiyies and toigonds
+wi2003 | 8g Data Appteatons ane Anayies
+W00a | Trendsin Data Saeree
+Total i
+TOTALCREDITS FORGRADUATION| 124
+#4 Pre-equisite.
+* Taken all Faculty and Programme Core Courses.
+Pass all Faculty and Programme Core Courses except for Industrial Training
+* Each Specialization Elective Course is only offered ONCE every academic session, either on Semester 1 OR Semester 2.
+
+### Page 224
+‘COURSE PLANNING FOR BACHELOR OF COMPUTER SCIENCE (DATA SCIENCE)
+"ACADEMIC SESSION 2025/2026
+[Revel [course Code [Semester eres
+‘eaaios | acbistipeinaasy Gana = {GIG1012" | Phiosophy and Curent issues (or loca student ond) Bas] >
+cata ‘Malay Lanqunae dor intemational student
+TuGo1 | Compuing Nemes x ‘6161004 [infomation Ltr
+{wix1002 [Fundamentals of Progamming 5 {6161005 | Socal Engagement z
+Wix1003_—[- Computer Sysiem and Organzation 3 Wia 12 —[ Data Stucke WTO) 5
+4 [WWAiGo1 —Tnformeton Siste x "wa009—[ Computer System Archecire (OWT) EI
+"wid3006—[ Machine Learning :
+"WiE7009—[Ineducion to Data Seance x
+etal | 6 Total |
+‘Course Code ‘Semester ‘credits | | Course code Semester? Credis
+Engish for Commrancation 1 3 {Go-Cumeutam: 2
+7 rs
+[wooo 7 conmuneaton Thnkna and Skits | Faro Toperatina Stems 4
+[- wnxzooe [Pred wananement 3] wnatoos —T network iz [——
+Wazoo 3 Spoclzaton Elective (1) 3
+2 |insoes— soe nos EI ‘Specalzaton Elecive 2) 3
+WHAKIOS —| Probably and Statics x Faculy Elstve 3
+Toa Total
+‘Semester ‘credits | | Course Code | ‘Semester 2 (indus | creas |
+‘wits001 | eta Sconce Project 3 Wirs002 [sta Science Industrial Training “
+‘Specaizaton Eecwwe ]™ EI
+‘Specalzaton Eecive 4)™ ra
+‘Spaaalzaton Eleciva(51* >
+Specaizaton Elecive (6)* 3
+a a
+Extamal Faculty Eiecive 2
+Eo Total | aa
+‘Course Component creas
+"W005 | Profesional Doweleament z Univers Courses, 20
+‘wnFi006 —[ Data Science and Applicaton” 5 Facully Core Courses cid
+‘4 [Litto —T nausea Sotston Development” S Focully Eocive Causes 6
+Programme Core Couses 33
+Specialization Elecve Couses 8
+Tear | "TOTAL CREDITS FOR GRADUATION | 124
+Prosoqusto
+“Taken al Faculty and Programme Core Courses except Academic Pret | and Academic Project I
+Pass all Faull and Programme Core Courses except fr indusial Trang and Academic Project I
+‘Specialization Elocive Courses wil be offoed ona rotation basis. Each Specelzaton Elecive sschodulod o run orly once in every academic session, ether in Semester tor Somestor 2
+
+
+## Master of Computer Science (Applied Computing) :: Programme Requirements
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 37-38
+
+### Page 37
+PROGRAMME REQUIREMENTS
+SS
+Programme Type
+The type of programme offered for the Master of Computer Science (Applied Computing) is a
+programme which shall consist of coursework (50%) and research leading to the submission of
+a dissertation in the candidate's area of study (50%).
+Admission Requirements
+- The general entry requirements to enrol in this program are as follows:
+Pass the Malaysian Certificate of Education (SPM)/equivalent with honours in
+Malay/Malaysian Language or honours in Malay/Malaysian Language of July Paper.
+- The special entry requirements to follow this program are as follows:
+Bachelor's degree with a CGPA of not less than 3.00 in the field of Computer
+‘Science/Information Technology/related fields;
+OR
+Bachelor's Degree with CGPA (2.70 — 2.99) in the field of Computer Science/Information
+Technology/related fields and meet at least one (1) of the following criteria
+i, Graduated from the University of Malaya
+ji, Have at least one (1) year of work experience in a related field
+ii, Produce publications in relevant fields
+iv, Scholarship recipient
+Vv, _ isan employee of a government agency.
+Vi, Pass the Faculty interview, or
+Vi, passed the faculty's special assessment.
+OR
+Other qualifications approved by the Senate from time to time.
+AND
+©) English Language Competency Requirements:
+‘+ Non-citizen applicants who obtained their degree from a university or institution of
+higher learning that does not use English as the medium of instruction for the degree
+in question who wish to follow a degree program and/or to write their dissertation in
+English are required to meet the following requirements:
+i. A minimum soore of $50 for the paper-based test (PBT), a score of 213 for the
+‘computer-based test (CBT) or a score of 80 for the internet-based test (iBT) for the
+Test of English as a Foreign Language (TOEFL);
+ii, Minimum band 6.0 for the International English Language Testing System (IELTS)
+(Academic);
+ili, Scores according to the respective program standards if higher than (a) and (b);,
+iv. For any program standard that places the TOEFL or IELTS (Academic) score lower
+than the University’s minimum soore, those programs must follow the minimum,
+score that has been set by the University;
+v. Minimum score of 57 Pearson Test of Academic English (PTE Academic);
+vi Minimum grade C for English subject in General Certificate of Education (A-Level);
+vii. Minimum grade C in B2 First by Cambridge Assessment English;
+vii, Minimum grade C in C1 Advanced by Cambridge Assessment English; or
+eon
+Oo®
+e
+Om
+
+### Page 38
+os
+ix. Minimum grade C in C2 Proficiency by Cambridge Assessment English.
+* Non-citizen applicants with the following backgrounds are exempt from the prescribed
+English language qualification requirements:
+i. Comes from a country where English is the national language;
+ii Possess an academic credential from an institution where English is the sole
+medium of instruction; or
+iii, Have studied in Malaysia and intend to pursue further education, subject to
+condition (b).
+Duration of Study
+The recommended study duration is between four (4) to eight (8) semesters.
+Programme Structure
+(1) The Master of Computer Science (Applied Computing) Programme will have forty-two
+(42) credits through coursework and dissertation.
+(2) Through Coursework and Dissertation Programme
+() The programme shall consist of two parts:
+(2) Part | comprises:
+(i) five (6) core courses, each three credits; and
+(ii) two (2) elective courses.
+(b) Part II shall consist of twenty-one (21) credits and shall involve
+research leading to the submission of a dissertation.
+(3) Details of courses offered shall be of those approved by the Senate from time to time
+‘on the recommendation of the Faculty and shall be made known to the candidates at
+the start of each session.
+(4) The list of Senate approved courses for the Master of Computer Science (Applied
+Computing) Programme shall be as indicated in List 1. Candidates shall be informed
+of the prescribed combination of courses for this programme prior to registration at the
+start of their study programme.
+ms.
+
+
+## Master of Computer Science (Applied Computing) :: Programme Objectives and Outcomes
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 39-40
+
+### Page 39
+r ca
+PROGRAMME OBJECTIVES & Q C
+OUTCOMES a
+oe
+PROGRAMME EDUCATIONAL OBJECTIVE (PEO)
+PEOA raduates able to establish themselves as competent and practicing professionals,
+in Computer Science or related fields._ (Professionalism)
+raduates able to continuously pursue new knowledge to improve their competency]
+PEO 2 [Pd subsequently work in teams to contribute to the industry or academia in
+Puter Science (Ongoing Personal Development)
+raduates able to contribute to sustainable development and the well-being of the
+PEOS ety through professional skills and ethics in the discipline of Computer Science
+(Societal Engagement)
+(Assessed after 3 - 5 years affer students graduated)
+PROGRAMME LEARNING OUTCOMES:
+Programme Learning Outcomes (PLO) ‘Cluster Learning Taxonomy
+‘Outcome (CLS) Category
+(KIPIA)"
+PLOT] Master the advanced concepts and the CLSt K
+latest theories in computer science. (Knowledge and
+Understanding)
+PLO2 | Apply problem solving skills and CLS2 K
+‘computer science knowledge for | (Cognitive skils)
+‘computing problems.
+PLOS | Integrate knowledge, techniques, skils, ‘CLS3A KP
+methodologies and appropriate |__ (Practical skills)
+technologies to create effective ICT
+solutions.
+PLO4 | Master the abilty to apply mathematical CLS3B KP
+skills in the area of computer science. (Digital and numerical
+skils)
+PLOS | Communicate effectively, verbally and in CLS3C PA
+writing, and able to work in ateam and | (Interpersonal and
+demonstrate leadership skills in carrying | communication)
+‘out computer solence related projects,
+PLOS [Demonstrate leadership that is CLS3D PA
+consistent with professional and ethical (Leadership,
+‘codes in computer science discipline autonomous and
+responsible)
+PLOT | Conceive technical and societal ‘CLS4 KA
+innovation through computer science (Personal and
+technologies. entrepreneurial skills)
+PLOS | Demonstrate character that in line with CLS5 KA
+professional ethical codes in computer (Ethics and
+science Professionalism)
+“Cognitive (K), Psychomotor (P), Affective (A)
+ms.
+
+### Page 40
+mart
+MATRIX OF MAPPING PLO TO PEO
+PEO1 PEO2 PEOS
+PLO1 qv |
+PLO2 v |
+PLO3 | v
+PLO4 | v
+PLOS | v
+PLOG Vv
+PLOT Vv
+PLOB | v
+
+
+## Master of Computer Science (Applied Computing) :: Candidature Requirements
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 41-41
+
+### Page 41
+“ce
+CANDIDATURE Q 2
+a
+REQUIREMENTS
+Fulfil the minimum candidature duration of 3 semesters.
+Fulfil the University language requirement (Bahasa Malaysia and English) no later
+than the second (2°) semester of candidature.
+| Fulfil the residential requirement of 6 months.
+Presentation
+© Proposal presentation at the beginning of the research component registration.
+Present research progress in a Candidature Defense session as required by
+the Faculty.
+
+
+## Master of Computer Science (Applied Computing) :: Graduate on Time (GOT) Schedule
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 42-42
+
+### Page 42
+GRADUATE ON TIME (G60T)
+SCHEDULE
+SS
+rh
+Q
+Semester Activities OutputiMilestone
+1 ‘ Appicabie to al intemational candidates: Atend Bahasa Melayu | OUTPUT OF SEM 1:
+course.
+‘+ Complete all core courses offered in Semester (inciuding | «Completed Bahasa Melayu course forall nternational candidates,
+Research Methodology) and 1 or 2 elective courses offered in | 2 Completed all selected courses,
+‘Semester 1.
+‘© Altend relevant workshops/ research seminars (E.9., © Corel oy relevent vortanoetieneersh
+EndNote, Tumitin). -
+2 ‘Complete ll core courses offered in Semester land 1or2 | OUTPUT OF SEM2:
+lective courses offered in Semester I.
+‘+ Register for dissertation and perform the folowing activites: | «Completed all selected courses.
++ Ghoose a research onic rom ait coated by ‘© Appointed supervisor and identified research topic.
+programme coordinator. i Daler
+‘© Submit appointment of supervisor form tothe office by the rae commit eraeerioel he
+Goatne Goan by hetecaaye ‘* Presented and passed Proposal Defence.
+‘© Prepare Proposal Defence report.
+‘+ Conduct Proposal Defence presentation.
+«Ifthe research includes human participant, apply for
+ethics approval
+‘+ Submit progress report
+3 ‘Register for dissertation and perform the folowing ectviies: | OUTPUT OF SEM 3:
+‘* Collect data/conduct experiment.
+‘© Analyse data © Collected data,
+‘* Prepare Candidature Defence report. © Analysed data
+‘* Conduct Candidature Defence presentation. ‘© Completed Candidature Defence report.
+‘© If passed Candidature Defence, prepare a draft of
+ph case ‘© Presented and passed Candidature Defence.
+& 'Sibrwa procrwesTenent ‘Draft ofthe dissertation reviewed by the Supervisor.
+4 ‘© Register for dissertation and perform the folowing activites: | OUTPUT OF SEM 4:
++ Submit dissertation for examination.
++ Make corrections based on examiner's feedback, if | Submitted dissertation for examination.
+applicable. ‘© Outcome of Committee of Examiners meeting.
++ Submit final dissertation for Senate approval. ‘© Received Senate letter.
++ Submit a progress report.
+Notes:
+Monitoring Panel
+1. The supervisor appoints a chairperson and 2 members who are experts in the field. A fourth member i
+necessary.
+2. The same panel should follow through with the Proposal and Candidature Defence.
+3. tis strongly recommended that one member be appointed as the internal examiner.
+4, The main responsibilities of the panels are to advise the student in improving the research.
+a
+g°
+(3
+allowed to be appointed if
+
+
+## Master of Computer Science (Applied Computing) :: Course Plan
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 43-44
+
+### Page 43
+vee
+COURSE PLAN ~ ~ .
+INTAKE SEMESTER | 2025/2026
+MASTER OF COMPUTER SCIENCE Credits | Semester! | Semester tt | Semester
+(APPLIED COMPUTING) 2025/2026 | 2025/2026 | 2026/2027
+Core Courses
+wox7001 __| *Research Methodology 3 a
+woa7001 _| Advanced Algorithms 3 v
+woar7015 —_| Advanced Machine Leaming 3 v
+woa7016 | Cloud Computing 3 y
+woarer7 _| Seeunty Rsk Anais and 3 r
+woc7024 _| Dissertation 2 ca
+Elective Courses [Students are required to choose any two (2) courses from the list below]
+woa7018 —_| Autonomous Robotics 3 v
+woa7019 _| Augmented Reality 3 y
+Framework-Based Software /
+Woc7014 | Design and Development : ~
+woc7020 _| Advanced Internet of Things 3 v
+wan7003 —_| Data Analytics 3 v
+* Students are required to register for the Research Methodology course in their first semester
+** Students are only allowed to register for a Dissertation after completing six (6) credits of coursework.
+Note: The courses that will be offered every semester are subject to change, depending on the availability of
+staff and the number of students registering
+ms.
+
+### Page 44
+COURSE PLAN
+Sse
+INTAKE SEMESTER II 2025/2026
+‘MASTER OF COMPUTER SCIENCE. credits | Semesterit | Semester! | Semester
+(APPLIED COMPUTING) 2025/2026 | 2026/2027 | 2026/2027
+Core Courses
+wox7001 _| *Research Methodology 3 v
+woa7001__ | Advanced Algorithms 3 v
+WOA7015 _| Advanced Machine Learning 3 Y
+WoA7016 | Cloud Computing 3 v
+woaror7 _| Sesuriy Risk Analyse and 5 F
+WoC7024 _| Dissertation 2 aa sal
+Elective Courses [Students are required to choose any two (2) courses from the list below]
+WoA7018 _ | Autonomous Robotics 3 ¥
+woa7019 | Augmented Reality 3 v
+WOC7020__| Advanced Internet of Things 3 #
+wan7003 _| Data Analytics 3 v
+* Students are required to register for the Research Methodology course in their first semester
+** Students are only allowed to register for a Dissertation after completing six (6) credits of coursework
+Note: The courses that will be offered every semester are subject to change, depending on the availabilty of
+staff and the number of students registering
+a
+_ ie
+mm”
+
+
+## Master of Computer Science (Applied Computing) :: List of Courses and Contents
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 45-50
+
+### Page 45
+LIST OF COURSES
+& CONTENTS
+ms
+Q
+CORE COURSES
+Code ‘Courses Credits
+Wox7001* | Research Methodology* $s
+woa7001 | Advanced Algorithms 3
+woa7015_ | Advanced Machine Learning 3
+WOA7016 | Cloud Computing 3
+woa7017 | Security Risk Analysis and Evaluation 3
+woc7024_| Dissertation** 24
+ELECTIVE COURSES
+(NOTE: Students are required to choose any two (2) courses from the lists below)
+Code
+Courses
+Credits
+WOA7018
+woc7014
+W0A7019
+woc7020
+'WQD7003,
+‘Autonomous Robotics
+Framework-Based Software Design and Development
+Augmented Reality
+Advanced Internet of Things
+Data Analytics
+eo ewe
+Note:
+* Students are required to register for the Research Methodology course in their first semester.
+** Students are only allowed to register for Dissertation after completing 6 credits of coursework.
+The courses that will be offered every semester are subject to change, depending on the availability of
+staff and the number of students registering.
+ms.
+
+### Page 46
+eon
+WOX7001 —_Research Methodology Q 2
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Describe appropriate methodologies used in computer science and information technology
+research.
+2. Devise a plan to be carried out within a feasible duration for answering research problems and
+questions identified.
+3. Demonstrate attitude and character in line with professional and ethical codes in computer
+science and information technology research.
+Synopsis of Course Content
+This course gives an overview of the dimensions of research in computer science and information
+technology. Major considerations and tasks in conducting research in the areas such as review of
+literature, identify problem statement, formulate research questions and objectives, select an
+appropriate approach or method to the research, plan and manage the research, tools for research,
+data analysis, and writing and presentation strategies, will be discussed too.
+Evaluation and Weightage
+Continuous Assessment : 100%
+Final Examination : 0%
+'WOA7001 Advanced Algorithms
+Course Learning Outcomes*
+At the end of the course, students are able to:
+1. Explain major algorithms and data structures.
+2. Implement the algorithms and data structures to solve real-world problems.
+3. Develop ICT solutions with algorithms and data structures.
+Synopsis of Course Content
+This course introduces students to the analysis and design of computer algorithms. Students will learn
+advanced design techniques, important classical algorithms and data structures, and their
+implementation in modern programming environments.
+Evaluation and Weightage
+Continuous Assessment : 60%
+Final Examination : 40%
+WOA7015_— Advanced Machine Learning
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Practice concepts and techniques for machine learning related to digital and numerical methods.
+2. Report the solution to machine learning problems by devising and listing the steps in machine
+a leaming applied to solve different types of problems
+3)
+Demonstrate skills and knowledge on machine learning by managing a machine learning project
+(3
+
+### Page 47
+os
+Q
+Synopsis of Course Content
+This course introduces advanced concepts and techniques for machine learning. It covers topics such
+as linear and logistic regression, decision tree, neural network, and support vector machines as well
+as reinforcement learning.
+Evaluation and Weightage
+Continuous Assessment 2 50%
+Final Examination + 50%
+WOA7016 Cloud Computing
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Explain the main concepts, key technologies, architecture and issues of cloud computing.
+2. Apply appropriate solutions to solve and manage complex problems in cloud computing.
+3. Deploy cloud applications using popular cloud platforms.
+‘Synopsis of Course Content
+This course is designed to introduce students to the emerging issues related to cloud computing. This
+course will examine several aspects of the cloud such as concepts related to cloud computing
+technologies, cloud models, cloud platform, virtualisation and orchestration, web services and cloud
+storages. This course also emphasises on practical implementations in developing and deploying
+cloud applications.
+Evaluation and Weightage
+Continuous Assessment : 50%
+Final Examination : 50%
+WOA7017__ Security Risk Analysis and Evaluation
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Explain the concepts of security risk assessment.
+2. Apply suitable security risk assessment methods.
+3. Evaluate a particular security risk assessment method.
+‘Synopsis of Course Content
+This course introduces the concepts and techniques used in security risk analysis and evaluation. It
+includes a comprehensive explanation of the six basic phases of security risk assessment, i.e. project
+definition, project preparation, data gathering, risk analysis, risk mitigation, and risk reporting and
+resolution. The course also explains several risk assessment methods and describes techniques to
+measure the effectiveness of a particular method.
+Evaluation and Weightage
+Continuous Assessment : 50%
+Final Examination : 50%
+ms.
+
+### Page 48
+WOC7024__—Dissertation Q
+Course Learning Outcomes a
+At the end of the course, students are able to:
+1. Report the literature review related to the proposed research project in the approved area.
+2. Implement a detailed research project based on the proposed research.
+3. Produce a dissertation of the research project
+‘Synopsis of Course Content
+The dissertation is concerned with the guidance rendered by the supervisor to the student on the proper
+way of conducting a software engineering, computer science or information technology research
+project, which could be in the form of face-to-face discussion, presentation, demonstration and
+communication. The dissertation also covers the identification of problem statements, understanding
+and formulation of the research objectives and research methodology to perform the research project
+Evaluation and Weightage
+Continuous Assessment : 100%
+Final Examination : 0%
+*Students have to pass candidature seminars (proposal defence and candidature defence) before
+‘submitting a dissertation for examination. Results of candidature seminars will be emailed to the
+students by the faculty.
+"Dissertation will be examined by examiners. The final results will be decided by the committee of
+examiners
+WOA7018 — Autonomous Robotics
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Discuss the fundamental principles of autonomous robot.
+2. Design autonomous robots with bio-inspired Intelligence, deep neural networks and deep
+reinforcement learning.
+3. Discuss the aspects of artificial intelligence and autonomous robotics systems from industrial 4.0
+perspectives.
+‘Synopsis of Course Content
+This course will present an introduction to autonomous robots from both academic and industrial
+viewpoints. For the academic part, emphasis will be given to recent advances in cognitive robotics,
+deep reinforcement learning, which combines deep neural networks with reinforcement learning to
+provide a framework for discovering suitable control actions (policies) and addressing complex tasks
+without explicit programming. For the industry-focused lectures, aspects of artificial intelligence and
+autonomous robotics systems will be considered from industrial 4.0 perspectives.
+Evaluation and Weightage
+Continuous Assessment : 50%
+Final Examination : 50%
+ms.
+
+### Page 49
+Q
+a.
+WOC7014 —_—- Framework-Based Software Design and Development %)
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Identify the basic principles of framework-based software design and development.
+2. Design a framework-based software system.
+3. Construct a framework-based innovative software project using associated programming
+language
+Synopsis of Course Content
+This course introduces the design and development of software using framework. It includes
+specification, implementation and configuration of an innovative software according to a specific
+framework, Students will learn the framework's programming language as well as the facilities
+provided by the framework.
+Evaluation and Weightage
+Continuous Assessment : 60%
+Final Examination + 40%
+WOA7019 Augmented Reality
+Course Learning Outcomes
+At the end of the course, students are able to:
+Describe the technologies related to Augmented Reality.
+Apply the related new technologies in the design of augmented reality applications.
+Develop interactive augmented reality applications for both PC based and mobile devices using a
+variety of input devices.
+‘Synopsis of Course Content
+This course is designed to introduce students with knowledge related to augmented reality concepts
+and technology. This is followed with a discussion on how knowledge about human sensory systems
+can facilitate in designing ergonomic augmented reality devices that match human perceptual
+capabilities. Students are then trained to develop an augmented application using a suitable
+programming language and 3D software. Towards the end of the course, there will be discussions on
+several examples of augmented reality applications with emphasis on the contributions of the
+augmented reality technology and future direction of this technology.
+Evaluation and Weightage
+Continuous Assessment : 50%
+Final Examination : 50%
+'WOC7020 = Advanced Internet of Things
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Explain the architecture and key technologies of the Internet of Things.
+2. Identify the challenges in the implementation of the Internet of Things.
+3. Solve problems related to the Internet of Things in wireless communications.
+‘Synopsis of Course Content
+This course is designed to introduce to students the emerging issues related to the Internet of Things.
+This course will examine several aspects of the Internet of Things such as application areas related to
+the Intemet of Things technologies, real-time models, local sensors, network components and
+vee
+Q
+
+### Page 50
+mm”
+One
+application-level components. This course also emphasises on solving problems related to wireless
+communications in developing and deploying the Internet of Things.
+Evaluation and Weightage
+Continuous Assessment: 50%
+Final Examination : 50%
+'WQD7003__— Data Analytics
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Explain the concepts of data analytics.
+2. Use suitable techniques for data pre-processing.
+3. Apply data analytics and machine learning techniques to solve real-world problems.
+Synopsis of Course Content
+This course aims to develop students’ ability to describe, explore and analyze data using suitable data
+analytics techniques
+Evaluation and Weightage
+Continuous Assessment : 60%
+Final Examination : 40%
+
+
+## Master of Software Engineering (Software Technology) :: Programme Requirements
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 52-53
+
+### Page 52
+PROGRAMME REQUIREMENTS
+SS
+iy
+1. Programme Type
+The Master of Software Engineering (Software Technology) programme which shall consist of
+coursework and research leading to the submission of a dissertation in the candidate's area of
+study, whereby fifty percent (50%) of the total number of credits shall be for research.
+2. Admission Requirements
+- The general entry requirements to enrol in this programme are as follows:
+Pass the Malaysian Certificate of Education (SPM)/equivalent with honours in
+Malay/Malaysian Language or honours in Malay/Malaysian Language of July Paper.
+- The special entry requirements to follow this programme are as follows:
+Bachelor's Degree with a CGPA of not less than 3.00 in the field of Computer
+‘Science/Information Technology/related fields;
+OR
+Bachelor's Degree with a CGPA of 2.70 — 2.99 in the field of Computer Science/Information
+‘Technology/related fields and meet at least one (1) of the following criteria:
+i. Graduated from Universiti Malaya
+ii, Has at least one (1) year of working experience in a related field
+ii, Has produced publications in the relevant fields
+iv. Scholarship recipient
+v. _ Is anemployee of a government agency
+vi. Pass the faculty's interview; or
+vi. Pass the faculty's special assessment
+OR
+‘Other qualifications approved by the Senate from time to time
+AND
+- English Language Competency Requirements
+© Non-citizen applicants who obtained their degree from a university or institution of
+higher learning that does not use English as the medium of instruction for the degree
+in question, who wish to follow a degree programme andlor to write their dissertation
+in English, are required to meet the following requirements:
+i. Amminimum score of 550 for the Paper-Based Test (PBT), a score of 213 for
+the Computer-Based Test (CBT) or a score of 80 for the Internet-Based Test
+(IBT) for the Test of English as a Foreign Language (TOEFL);
+ii, Minimum band 6.0 for the International English Language Testing System
+(IELTS) (Academic);
+ili, Scores according to the respective programme standards if higher than i, and
+it;
+iv. For any programme standard that places the TOEFL or IELTS (Academic)
+score lower than the University's minimum score, those programmes must
+follow the minimum score that has been set by the University;
+Vv. _ Minimum soore of 57 Pearson Test of Academic English (PTE Academic);
+
+### Page 53
+iy
+vi. Minimum grade C for English subject in General Certificate of Education (A-
+Level);
+vi Minimum grade C in B2 First by Cambridge Assessment English;
+vil, Minimum grade C in C1 Advanced by Cambridge Assessment English; or
+ix. Minimum grade C in C2 Proficiency by Cambridge Assessment English
+¢ Non-citizen applicants with the following backgrounds are exempt from the prescribed
+English language qualification requirements
+i. Comes from a country where English is the national language:
+ii, Possess an academic credential from an institution where English is the sole
+medium of instruction; or
+ii, Have studied in Malaysia and intend to pursue further education, subject to
+condition ii,
+Duration of Study
+The recommended study duration is between four (4) to eight (8) semesters.
+Programme Structure
+(1) The Master of Software Engineering (Software Technology) Programme consisting of
+coursework and dissertation shall consist of forty-two (42) credits comprising two parts,
+namely:
+(a) Part | which consists of
+(i) five (5) core courses, each three credits;
+and
+(ii) two (2) elective courses, each three credits
+(b) Part iI which consists of twenty one (21) credits, shall consist of research leading
+to the submission of a dissertation.
+(2) Details of courses offered are of those approved by the Senate from time to time on the
+recommendation of the Faculty and shall be made known to the candidates at the start
+of each session
+(3) The list of Senate approved courses for the Master of Software Engineering
+(Software Technology) is as indicated in List 1. Candidates shall be informed of the
+prescribed combination of courses for this programme prior to registration at the start of
+their study programme
+
+
+## Master of Software Engineering (Software Technology) :: Programme Objectives and Outcomes
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 54-55
+
+### Page 54
+oy
+=)
+PROGRAMME OBJECTIVES &
+OUTCOMES
+oe
+PROGRAMME EDUCATIONAL OBJECTIVE(S) (PEO)
+Graduates would have established themselves as practising professionals in software
+PEO 1 | engineering or related areas. (Professionalism)
+Graduates able to continuously pursue new knowledge to improve their competency
+PEO 2 | and subsequently work in teams to contribute to the industry or academia in software
+engineering. (Ongoing Personal Development)
+Graduates have contributed to sustainable development and the well-being of the
+PEO 3 _| society through professional skills and ethics in the discipline of software engineering.
+(Societal Engagement)
+(Assessed after 3 - 5 years after students graduated)
+PROGRAMME LEARNING OUTCOME(S) (PLO)
+At the end of Master of Software Engineering (Software Technology) programme, graduates are able
+to
+MQF Cluster of | Taxonomy
+No. Programme Learning Outcome(s) (PLO) ‘Learning Category
+Outcomes (KIP/Ay"
+rior | Master the advanced concepts and the latest iRnselecbs “a '
+theories in software engineering liebe in
+‘Apply problem solving skills and software ae
+PLO2 ergnecring knowledge to solve real-world | oantive Skis) K
+‘Analyse, design, develop and maintain software
+Log | Solutions by applying software engineering CLS3A eB
+principles, standards, methods, techniques and | (Practical Skills) 7
+tools with the aim to engineer quality software.
+CLs3B
+Master the ability to apply mathematical skills in the
+PLO4 (Digital ana KP
+software development life cycle. Nuneracy Sle)
+Communicate effectively, verbally and in witing, | inter osscral and
+PLOS | and able to work in team in carrying out software | ('erpersonal any PA
+engineering projects Ski
+ills)
+Demonstrate leadership that is consistent with jiectonth
+PLO6 | professional code of ethics in software engineering Prsiestie em PA
+cae ale Responsibility)
+a
+
+### Page 55
+discipline
+cLs4
+PLo7 | Practice technical and societal innovation through (Personal and RA
+software engineering technologies. Entrepreneurial
+Skills)
+Demonstrate characters that are in line with LSS
+PLO8 _| professional code of ethics in software engineering (Ethics and KA
+Professionalism)
+‘*K - Cognitive; A - Affective; P - Psychomotor
+MATRIX of MAPPING OF PLO to PEO.
+PLO
+PEO
+PEO1 PEO2 PEOS
+PLO1
+PLo2
+PLO3
+PLO4
+PLOS
+PLoS
+PLO7
+PLos
+
+
+## Master of Software Engineering (Software Technology) :: Candidature Requirements
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 56-56
+
+### Page 56
+CANDIDATURE
+REQUIREMENTS
+Master of Software Engineering (Software Technology)
+No Requirement
+1. | Fulfil the minimum candidature duration of 4 semesters.
+2, _| Fulfil the University language requirement (Bahasa Malaysia and English) not later
+than the second (2nd) semester of candidature.
+3. _ | Fulfil the residential requirement of 6 months.
+Presentation
+‘* Proposal Defence at the beginning of the research component registration.
+4. | © Present research progress in a Candidature Defence session as required by
+the Faculty.
+
+
+## Master of Software Engineering (Software Technology) :: Graduate on Time (GOT) Schedule
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 57-57
+
+### Page 57
+cae
+GRADUATE ON TIME(GOT)
+SCHEDULE
+‘Semester Activities ‘Output/Milestone
+Attend Bahasa Melayu course (applicable ‘Completed Bahasa
+to international candidates), Melayu course (applicable
+‘© Complete all core courses offered to international
+(including Research Methodology), and 1 candidates).
+oF 2 elective courses offered in the current ‘Completed all selected
+1 semester. courses.
+* Attend relevant workshops/research ‘Completed relevant
+seminars (e.g., EndNote, Turnitin). workshops/research
+‘© Start thinking of research area for seminars,
+dissertation ‘Some idea of research
+area for dissertation.
+‘* Complete all core courses offered, and 1 ‘Completed all selected
+oF 2 elective courses offered in the current courses.
+semester. Potential research topic
+‘¢ Register for the Dissertation course and Supervisor appointment
+perform the following activities: ‘Completed Proposal
+© choose a research topic from a list Defence report.
+collated by programme coordinator |e Presented and passed
+or propose own research topic to Proposal Defence
+potential supervisor. The research | ¢ Obtained ethics approval
+topic must include Software (if applicable).
+Engineering research element. Submitted progress report
+© Appoint a supervisor for
+dissertation in the first semester
+the student registered for the
+Dissertation course. This is done
+2 by submitting the Appointment of
+‘Supervisor form (which includes a
+tentative dissertation topictttle
+agreed by the supervisor) to the
+faculty's Postgraduate Office by
+the stipulated deadiine (which is
+usually no later than the 7th week
+of a semester)
+© Prepare for Proposal Defence
+(report and presentation),
+© Conduct Proposal Defence
+presentation
+Re-do Proposal Defence if failed.
+‘Apply for ethics approval if the
+research involves human
+participants and/or animals.
+© Submit progress report
+
+
+## Master of Software Engineering (Software Technology) :: Course Plan
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 59-61
+
+### Page 59
+cae
+COURSE PLAN
+INTAKE SEMESTER | 2025/2026
+MASTER OF SOFTWARE ENGINEERING ‘Sem Semit ‘SemI
+(SOFTWARE TECHNOLOGY) Credits | 2025/2026 | 2025/2026 | 2026/2027
+Core Courses
+wox7001* | Research Methodology 3 v
+‘Architecting Software
+wocroo | Srchtect 3 v
+Framework Based
+woc7014 | Software Design and 3 v
+Development
+Software Verification and 3 qi
+WoC7015 _| Validation =
+Software Project 3 j
+woor0t | Nanagement V
+a Dissertation (P1) 9 vn
+WOC7024 v=
+eH Dissertation (P2) 2
+Elective Courses [Students are required to choose any 2 courses from the list below]
+‘Advanced Machine
+woaro1s | Tesmning 3 v
+woaroi7 _| Seeunly Risk Analysis and A rT
+woc7017 | Big Data Processing 3 V
+woc7018 | Requirements Engineering 3 v
+waernis | peri Pmerene evn 3 ]
+Woo hae Intemet of 3 r
+* Students are required to register for the Research Methodology course in their first semester
+“ Students are only allowed to register for a Dissertation after completing six (8) credits of
+coursework and have taken or taking WOX7001 Research Methodology.
+Note: The courses that will be offered every semester are subject to change, depending on the
+availability of staff and the number of students registering.
+
+### Page 60
+INTAKE SEMESTER Il 2025/2026
+kK
+Things.
+MASTER OF SOFTWARE ENGINEERING Semil Semi Sem tt
+(SOFTWARE TECHNOLOGY) Credits | 2025/2026 | 2026/2027 | 2026/2027
+Core Courses
+Wox7001* | Research Methodology 3 v
+Architecting Software
+woo7004_| Systems 3 v
+Framework Based
+‘woc7014 Software Design and 3 ci
+Development
+Software Verification and 3
+WOC7015_| Validation ¥
+‘Software Project 3
+woc7016 | ianagement v
+en Dissertation (P1) 9 ve
+baa Dissertation (P2) 12 ve
+Elective Courses [Students are required to choose any 2 courses from the list below]
+‘Advanced Machine
+woar018 | (esming 3 v
+‘Security Risk Analysis and
+WOATO17 _| Evaluation i i
+woc7017 _| Big Data Processing 3 v
+WOC7018 | Requirements Engineering 3 qv
+User Experience Design 7
+WoC7019 | Studio 3 V
+woo7o20 | Advanced Intemet of 3 7
+* Students are required to register for the Research Methodology course in their first semester
+* Students are only allowed to register for a Dissertation after completing six (6) credits of
+coursework and have taken or taking WOX7001 Research Methodology.
+Note: The courses that will be offered every semester are subject to change, depending on the
+availability of staff and the number of students registering.
+Om
+
+### Page 61
+yy
+IMPORTANT NOTES ON MASTER OF SOFTWARE ENGINEERING (SOFTWARE
+TECHNOLOGY) RESEARCH METHODOLOGY COURSE AND DISSERTATION COURSE .
+* Research Methodology course (WOX7001):
+* Students are required to register for the Research Methodology course in their first semester.
+** Dissertation course (WOC7024 for intake Sem 1 2023/2024 onwards; WOC7021 for intake
+2021/2022 and 2022/2023):
+© Registration of Dissertation course
+© Students can only start to register to take the Dissertation course if they have fulfilled the
+following pre-requisite of the Dissertation course:
++ Have passed any two courses (6 credits) (excluding language courses)
++ Have taken or taking WOX7001 Research Methodology.
+© After registering to take the Dissertation course for the first time, a student has to register
+for the Dissertation course in every subsequent semester as long as he/she has not
+submitted the final dissertation for Senate approval, or he has not obtained approval from
+the faculty for withdrawing from the programme for that semester.
+© Appointment of Dissertation Supervisor
+© Students must appoint supervisor for their dissertations in the first semester they register
+for the Dissertation course.
+© The Appointment of Supervisor form (which includes a tentative dissertation topicititle
+agreed by the supervisor) should be submitted to the faculty's Postgraduate Office by the
+stipulated deadline (which is usually no later than the 7th week of a semester)
+© Asstudent must get the respective supervisor's approval and signature before submitting
+the Appointment of Supervisor form to the faculty's Postgraduate Office.
+© Ifa student has registered for the Dissertation course but has not appointed a
+supervisor for his/her dissertation, the student will not be able to submit his/her
+Progress Report for Dissertation. See next paragraph.
+© Submission of Progress Report for Dissertation
+© Ifa student has registered to take the Dissertation course in a particular semester, he/she
+has to submit the Progress Report for Dissertation for that semester via the Maya system.
+© The deadline to submit the Progress Report is different in each semester and will be
+announced by the university/faculty. The students are responsible for monitoring their
+email accounts to check the email regarding the deadline and have to submit their
+Progress Report before the deadline.
+© Students who did not submit the Progress Report by the deadline will obtain
+“Unsatisfactory” for their Dissertation for that semester. This will affect renewal of
+viva for international students.
+© Submission of Dissertation for Examination
+© Students cannot submit their dissertations for examinations if their CGPA is below 3.0 or if
+they have not completed Part 1 (Coursework).
+
+
+## Master of Software Engineering (Software Technology) :: List of Courses and Contents
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 62-68
+
+### Page 62
+iy
+LIST OF COURSES &
+CONTENTS
+CORECOURSES
+Code Course Credits
+wox7001_| Research Methodology 3
+W007004_| Architecting Software Systems 3
+W0C7074_| Framework Based Software Design and Development 3
+W0O7015_| Software Verification and Validation 3
+W0O7016_| Software Project Management 3
+ar aa Dissertation (P1) 9
+i Dissertation (P2) 12
+ELECTIVE COURSES
+(Note: Students are required to choose any two (2) courses from the list below)
+Code Course Credits
+W0G7017 _| Big Data Processing 3
+W0C7018_| Requirements Engineering 3
+WOC7019_| User Experience Design Studio 3
+W007020_| Advanced Internet of Things 3
+WOAT015_| Advanced Machine Learning 3
+WOA7017 _| Seourty Risk Analysis and Evaluation 3
+The courses that will be offered every semester are subject to change, depending on the availabilty of
+staff and the number of students registering.
+Please read the “Important Notes on Master of Software Engineering (Software Technology)
+Research Methodology course and Dissertation course”.
+
+### Page 63
+cae
+WOX7001 Research Methodology
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Describe appropriate methodologies used in computer science and information technology
+research.
+2. Devise a plan to be carried out within a feasible duration for answering research problems and
+questions identified.
+3. Demonstrate attitude and character in line with professional and ethical codes in computer
+science and information technology research.
+Synopsis of Course Content
+This course gives on overview of the dimensions of research in computer science and information
+technology. Major considerations and tasks in conducting research in the areas such as review of
+literature, identify problem statement, formulate research questions and objectives, select an
+appropriate approach or method to the research, plan and manage the research, tools for research,
+data analysis, and writing and presentation strategies, will be discussed too.
+Evaluation and Weightage
+Continuous Assessment : 100%
+Final Examination : 0%
+WOC7004 = Architecting Software Systems
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Apply different types of architectural styles/patterns in developing software systems.
+2. Design software architecture,
+3. Evaluate software architecture in a team
+Synopsis of Course Content
+This course covers advanced architecture design of software systems. It reviews the different
+architectural structures and views, quality attributes, tactics to achieve quality attributes and common
+architectural styles/patterns (such as layered, broker, client-server, peer-to-peer, service-oriented
+architecture, and so on). It covers documenting software architecture.
+This course also covers methods to design software architecture (e.g. Attribute-Driven Design
+method) and evaluate software architecture (e.g. ATAM analysis method). It also covers architecting
+software product lines, architecting in the Cloud, and supporting tool.
+Evaluation and Weightage
+Continuous Assessment : 60%
+Final Examination + 40%
+
+### Page 64
+iy
+WOC7014_ _— Framework-Based Software Design and Development
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Identify the basic principles of framework-based software design and development.
+2. Design a framework-based software system.
+3. Construct a framework-based innovative software project using associated programming
+language.
+Synopsis of Course Content
+This course introduces the design and development of software using framework. It includes
+specification, implementation and configuration of an innovative software according to a specific
+framework. Students will learn the framework's programming language as well as the facilities
+provided by the framework.
+Evaluation and Weightage
+Continuous Assessment : 60%
+Final Examination 40%
+'WOC7015 __ Software Verification and Validation
+Course Learning Outcomes
+At the end of the course, students are able to:
+4. Discuss the concepts, principles, and techniques of software verification and validation.
+2. Design test through appropriate evaluation of chosen techniques from requirements and
+specifications, design artefacts, or the source code.
+Calculate small program code behaviours for checking valid path
+Analyse software system behaviours statically through model checking and probabilistic
+properties of program codes
+ae
+Synopsis of Course Content
+This course introduces the students the concepts, principles, techniques, and tools of software
+verification and validation within modem software development together with its formal techniques.
+The course covers from test design and test plan in test driven development of agile to conduct tests
+using tools. The course also exposes the students the formal approach of static analysis and model
+checking in verifying uncertainty in software design models and requirements.
+Evaluation and Weightage
+Continuous Assessment : 50%
+Final Examination 1 50%
+
+### Page 65
+cae
+WOC7016 —_Software Project Management
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Write a software project management plan by addressing the issues of scope, time, cost,
+resource and quality.
+2. Manage a software project by demonstrating knowledge of project management techniques and
+skills.
+3. Demonstrate attitude and character in line with professional ethics by working on a team project
+as a project manager or active team member.
+Synopsis of Course Content
+This course provides an overview of project management principles, techniques and skills. This
+course covers topics to understand the genesis of project, program, and portfolio management and
+their importance to software projects. In particular, the main tasks involved in initiating, planning,
+executing, monitoring and controlling, and closing software projects. The topics also include the
+knowledge areas that can be applied to manage project integration, scope, time, cost, quality, human
+resource, communications, risk and procurement.
+Evaluation and Weightage
+Continuous Assessment : 60%
+Final Examination : 40%
+'WOC7024 __ Dissertation
+Course Pre-requisite(s)/Minimum Requirement(s)
+Have passed any two courses
+* Have taken or taking WOX7001 Research Methodology
+Course Learning Outcomes
+At the end of the course, students are able to:
+4. Report the literature review related to the proposed research project in the approved area.
+2. Implement a detailed research project based on the proposed research.
+3. Produce a dissertation of the research project.
+‘Synopsis of Course Content
+The dissertation is concerned with the guidance rendered by the supervisor to the student on the
+proper way of conducting a software engineering, computer science or information technology
+research project, which could be in the form of face-to-face discussion, presentation, demonstration
+and communication. The dissertation also covers the identification of problem statements,
+understanding and formulation of the research objectives and research methodology to perform the
+research project.
+Evaluation and Weightage
+Continuous Assessment 100%
+Final Examination 1 0%
+“Students have to pass candidature seminars (proposal defence and candidature defence) before submitting
+dissertation for examination. Results of candidature seminars will be emailed to the students by the faculty.
+“Dissertation will be examined by examiners. Final results will be decided by the committee of examiners,
+
+### Page 66
+iy
+WOC7017 _Big Data Processing
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Explain the concepts of big data technologies
+2. Apply parallel processing techniques for processing big data.
+3. Evaluate the suitability of different processing techniques for big data processing
+Synopsis of Course Content
+It becomes more and more difficult to handle the growing amount of data with traditional data
+processing methods. There are many parallel processing frameworks and systems have been
+introduced such as MapReduce, Hadoop, Pig, Hive, Spark and Twister. Many of these frameworks
+and systems can handle different kinds of big data problems. This course will review and analyse
+various processing systems, architectures, frameworks, programming languages and programming
+models and their capabilities for large-scale data. This course will also analyze the advantages and
+disadvantages of these processing paradigms within the scope of the big data.
+Evaluation and Weightage
+Continuous Assessment : 60%
+Final Examination : 40%
+WOC7018 —_ Requirements Engineering
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Describe current techniques used in core activities in software requirements engineering.
+2. Use suitable techniques and tools to develop software requirements specification to fulfill user
+requirements.
+3. Evaluate relevant research issues in improving requirements engineering process.
+Synopsis of Course Content
+This course covers core activities in requirements engineering process such as requirements
+elicitation, validation, management and negotiation and techniques, tools and methods for supporting
+those activities. It also discusses and explores relevant research issues in areas such as
+requirements prioritization, impact analysis, process change management and requirements
+traceability
+Evaluation and Weightage
+Continuous Assessment : 60%
+Final Examination : 40%
+
+### Page 67
+WOC7019 _—User Experience Design Studio
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Apply the principles, models and techniques emphasizing the design of user experience (UX) in
+Human Computer Interactive systems.
+2. Develop an Interactive Human Computer system that takes into consideration universal
+accessibility through Agile and LeanUX.
+3. Evaluate the usability of the interactive Human Computer system which includes ethical, societal
+and cultural factors.
+‘Synopsis of Course Content
+This course covers advanced topics related to the human cognition, psychology, software engineering
+formal methods principles, models and techniques to represent user and interactive environment.
+Development projects uses Agile and LeanUX methodology taking into consideration universal
+accessibility for different range of users such as novice to experts, children to elderly, normal to
+people with disabilities.
+Design and implementation of projects include web UX, mobile UX and other intelligent systems.
+Design and implementation concepts go beyond user interfaces to include sensors, controls,
+autonomous vehicles, ubiquitous computing in the context of Internet of Things (loT), social data
+analytics and visualization. Interactive input may involve gestures, voice, eye movement and facial
+expression.
+Evaluation of the implemented Human interactive system uses techniques such as expert review,
+heuristics, usability testing, acceptance test, survey, active observation or control environment.
+Factors that influence UX evaluation are related to ethical, societal and cultural as well as usability
+goals.
+Evaluation and Weightage
+Continuous Assessment : 100%
+Final Examination : 0%
+WOC7020_ = Advanced Internet of Things
+Learning Outcomes
+At the end of this course, the students are able to
+1. Explain the architecture and key technologies of internet of things.
+2. Identify the challenges in the implementation of internet of things.
+3. Solve problems related to internet of things in wireless communications.
+‘Synopsis of Course Content
+This course is designed to introduce to students the emerging issues related to internet of things, This
+course will examine several aspects of internet of things such as application areas related to internet
+of things technologies, real-time models, local sensors, network components and application-level
+components. This course also emphasises on solving problems related to wireless communications in
+developing and deploying internet of things.
+Evaluation and Weightage
+Continuous Assessment : 50%
+Final Examination : 50%
+
+### Page 68
+iy
+'WOA7015_ — Advanced Machine Learning
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Practice concepts and techniques for machine learning related to digital and numerical methods.
+2. Report the solution to machine learning problems by devising and listing the steps in machine
+learning applied to solve different types of problems
+3. Demonstrate skills and knowledge on machine learning by managing a machine learning project
+Synopsis of Course Content
+This course introduces advanced concepts and techniques for machine learning. It covers topics such
+as linear and logistic regression, decision tree, neural network, and support vector machines as well
+as reinforcement learning.
+Evaluation and Weightage
+Continuous Assessment : 50%
+Final Examination : 50%
+WOA7017 __ Security Risk Analysis and Evaluation
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Explain the concepts of security risk assessment.
+2. Apply suitable security risk assessment methods.
+3. Evaluate a particular security risk assessment method.
+Synopsis of Course Content
+This course introduces the concepts and techniques used in security risk analysis and evaluation. It
+includes a comprehensive explanation of the six basic phases of security risk assessment, i.e. project
+definition, project preparation, data gathering, risk analysis, risk mitigation, and risk reporting and
+resolution. The course also explains several risk assessment methods and describes techniques to
+measure the effectiveness of a particular method.
+Evaluation and Weightage
+Continuous Assessment : 50%
+Final Examination : 50%
+
+
+## Master in Data Science :: Programme Requirements
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 70-71
+
+### Page 70
+PROGRAMME REQUIREMENTS
+SS
+4. Programme Type
+The type of programme offered for the Master in Data Science is a programme consisting of 10
+coursework which prepares students for the final capstone project which allows students to
+apply the knowledge they learned in the taught courses into real world applications.
+2. Admission
+(a) Qualifications for Admission
+() A Bachelor's degree with Honours in Science stream with a minimum CGPA of
+3.30 or equivalent;
+OR
+(i) A Bachelor's degree with Honours or equivalent in non-Science stream with a
+minimum CGPA of 3.50 with work experience in related fields for at least three
+(3) years in:
+4. Business and Economics
+2. Statistics & Mathematics
+3. Accounting & Finance
+and meet at least one (1) of the following criteria:
+sa graduate of Universiti Malaya
+Has at least one (1) year of work experience in a related field
+Has produced publications in a related field
+Scholarship recipient
+is an employee of a goverment agency
+Passes the Faculty interview; or
+Passes the special assessment by the Faculty
+e@-paecm
+OR
+(ii) Other qualifications approved by the University Senate.
+(b) English Language Proficiency
+International candidates are required to.
+() Atleast IELTS Band 6 (Academic) or TOEFL score of 550 (paper based) / 213
+(computer based) / 80 (Internet based) / PTE Academic with minimum score
+57 / minimum a grade of C for the English subject in the General Certificate of
+Education (A-level) or Cambridge English: First (FCE) or Cambridge English
+Advance (ACE) or Cambridge English: Proficiency (CPE), if their first degree
+is from a university where English is not the medium of instruction
+3. Duration of Study
+The programme of study : two (2) semesters + one (1) special semester, to eight (8) semesters,
+4. Programme Structure
+‘The Master in Data Science Programme through coursework shall have a total of forty-
+two (42) credits.
+(a)
+
+### Page 71
+()
+()
+(d)
+The programme shall consist of two parts
+() Part consists of.
+= six (6) core discipline courses, comprise of three or four credits
+courses; and
+= three (3) elective courses, each four credits
+(i) Part Il consists of a ten (10) credits project and shall involve investigation and
+analysis of a real world case study, leading to the submission of a report.
+Details of courses offered shall be of those approved by the Senate from time to time
+‘on the recommendation of the Faculty and shall be made known to the candidates at
+the start of each session,
+The list of Senate approved courses for the Master in Data Science Programme shall
+be as indicated in List 1.
+
+
+## Master in Data Science :: Programme Objectives and Outcomes
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 72-74
+
+### Page 72
+PROGRAMME OBJECTIVES &
+OUTCOMES
+ee
+PROGRAMME EDUCATIONAL OBJECTIVES (PEO)
+1. Data Scientists who are knowledgeable and able to extract meaningful insights to help
+organizations cope with challenges and arising issues.
+2. Data Scientist who possesses interpersonal skills in delivering effective data science solutions
+for industry or other stakeholders.
+3. Data Scientist who engages and advocates lifelong learning activities with an entrepreneurial
+mindset for a suocessful career
+4, Data Scientist who can lead and contribute to data science teams in public or private
+organizations with a full sense of responsibilty and good ethics
+PROGRAMME LEARNING OUTCOMES (PLO)
+No. Programme Learning Outcomes PLOs Taxonomic
+Category
+. | Master the important concepts and theories in the field oF | pig "
+data science that can be utilized in relevant domains.
+2 [Recommend innovative solutions for problems in data
+science and scientific computing
+3 | Construct data science solutions and tools in terms of
+efficiency and effectiveness
+@_ | interact with various stakeholders clearly and confidently, to
+successfully implement group projects. or system | PLO4 Pp
+development efficiently and effectively
+© | Communicate effectively with diverse audiences by
+publishing and presenting data science solutions in the | PLOS P
+established academic or industrial platform
+6 | Utilise digital skills to acquire, interpret, and extend
+PLO2 K
+PLO3 Pp
+knowledge in data science. PLOG P
+7. | Apply data analytic skils to acquire, interpret, and extend
+knowledge in data science LO?! P
+[Demonstrate leadership, teamwork and responsibiiy im] 5 Og A
+delivering data science solutions
+9. | Exhibit skills and capabilities to extend relevant knowledge in PLO m
+data science through life-long learning
+70, | Demonstrate abiity to adopt an entrepreneurial mindset in
+the data science discipline REDO A
+77_ | Practice the philosophy, principles, and high ethical valuesin | > 5 a
+professional practices related to data science
+(List of 11 domains of learning outcomes in accordance with the MQF program.)
+
+### Page 73
+MATRIX OF MAPPING PLO TO PEO
+PEO
+PLO PEO1 PEO2 PEO3 PEO4
+PLO1
+PLO2
+PLOS x
+PLO4
+PLOS
+PLO6 x
+PLOT
+PLOS
+PLOS
+PLO10
+PLO11
+
+### Page 74
+Reference notes:
+‘The Domain of the MQF in Programme Learning Outcomes program (PLO)
+PO | Domain
+PLO1 | Knowledge and Understanding
+PLO2 Cognitive Skills
+PLO3__| Practical Skills
+PLO4 | Interpersonal Skills
+PLOS: Communication Skills
+PLO6 | Digital Skills
+PLO7 Numeracy Skills
+PLO8 | Leadership
+PLOS Personal Skills
+PLO10 | Entrepreneurial Skills
+PLO11 | Ethics and Professionalism
+Reference notes:
+Taxonomic Category
+K Cognitive
+A Affective
+P Psychomotor
+
+
+## Master in Data Science :: Course Plan
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 75-76
+
+### Page 75
+COURSE PLAN
+ee $$$ ao >
+OS
+INTAKE SEMESTER | 2025/2026
+Semester! | Semesterll | Semester ll
+MASTER IN DATA SCIENCE cons | See! | eee |) ee
+Core Courses
+Research
+wox7oo1 | feeeat 3 y
+Principles of Data
+waoroor | Ernciple 3 v
+wan7003 | Data Analytics 3 y
+Programming for
+Wa07004 | Data Science 4 q
+Big Data
+waoro07 | Foe ant 3 v
+Applied Machine
+wao7or2 | Peeing 4 v
+wap702s_ | *Data Science 10 y Y
+Research Project
+Elective Courses [Students are required to choose any 3 courses from the list below]
+WAQD7005 | Data Mining 4 Vv
+Parallel and a v
+Wan7008 | Distributed
+‘Computing
+Big Data 4 Tv
+Wan7009 | Applications &
+Analytics
+Network and 4 v
+wa07010 | Security
+Statistics for Data 4 Vv
+wan7013 | Scarce
+Natural Language a Tv
+WOF7007_| Processing
+Note:
+“Students are only allowed to register for WQD7025 Data Science Research Project after completing at
+least three (3) core discipline courses (including WOX7001).
+For Data Science Research Project (P1 and P2) must complete the project in consecutive semesters.
+Example
+* P1 in Semester |I and P2 in Special Semester
+* P1 in Special Semester and P2 in Semester |
+Pt in Semester | and P2 in Semester II
+Not all courses will be offered every semester; the actual courses offered will depend on the availability of
+staff and the number of students registering.
+Oma
+
+### Page 76
+INTAKE SEMESTER II 2025/2026
+Semester il | Semester ill | Semester |
+MASTER IN DATA SCIENCE Giese || eee | Seen | eee
+Core Courses
+wox7001 | Research Methodology ] 3 v
+Principles of Data
+waproor | Enns 3 v
+WaD7003 | Data Analytics 3 v
+Programming for Data
+wanroo4 | Progra 4 v
+wan7007 | BigData Management | 3 v
+‘Applied Machine
+wao7or2 | ApEn 4 v
+wap7025. | “Data Science 10 v v
+Research Project
+Elective Courses [Students are required to choose any 3 courses from the list below]
+wap7005. | Data Mining 4 v
+wanrcoe | Peete pa Destrbuted |g 7
+wanrooe | 89 Gata APpteatons& [ 7
+wa07010 | Network and Security 4 v
+weonns: | Exiwere Ose 4 v
+WarF7007 sa ee 4 ¥
+Note:
+“Students are only allowed to register for WQD7025 Data Science Research Project after completing at
+least three (3) core discipline courses (including WOX7001).
+For Data Science Research Project (P1 and P2) must complete the project in consecutive semesters.
+Example:
+© P1 in Special Semester and P2 in Semester |
+* P1 in Semester il and P2 in Special Semester
+‘© P14 in Semester | and P2 in Semester II
+Not all courses will be offered every semester; the actual courses offered will depend on the availabilty of
+staff and the number of students registering
+
+
+## Master in Data Science :: List of Courses and Contents
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 77-82
+
+### Page 77
+LIST OF COURSES &
+CONTENTS
+CORE COURSES
+Code Course Credits
+Wox7001 | Research Methodology 3
+Wap7001 | Principles of Data Science 3
+Wap7003 | Data Analytics 3
+Wap7004 | Programming for Data Science 4
+wan7007 | Big Data Management 3
+wap7012 | Applied Machine Learning 4
+*wap7025 | Data Science Research Project 40
+ELECTIVE COURSES
+(NOTE: Students are required to choose any three (3) courses from the list below)
+Code Course Credits
+wan7005 | Data Mining 4
+wap7008 | Parallel and Distributed Computing
+wan7009 | Big Data Applications & Analytics
+wap7010 | Network and Security
+WaD7013 _| Statistics for Data Science
+WQF7007 _ | Natural Language Processing
+pean
+Note :
+* Students are only allowed to register for WQD7025 Data Science Research Project after
+completing at least three (3) core discipline courses (including WOX7001).
+Not all courses will be offered every semester; the actual courses offered will depend on the
+availability of staff and the number of students registering.
+
+### Page 78
+wox7001 Research Methodology
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Analyze the problem solving skills and computer science knowledge to solve real-world problems
+using the correct research methodology.
+2. Plan effective communication, verbally and in writing, and be able to work in a team and
+demonstrate leadership skills in carrying out computer science related projects.
+3. Show an attitude and character in line with professional and ethical codes in computer science.
+‘Synopsis of Course Content
+This course gives an overview of the dimensions of research in computer science and information
+technology. Major considerations and tasks in conducting research in the areas such as review of
+literature, identify problem statements, formulate research questions and objectives, select an
+appropriate approach or method to the research, plan and manage the research, tools for research,
+data analysis, and writing and presentation strategies, will be discussed too.
+Evaluation and Weightage
+Continuous Assessment 5 100%
+WQD7001 _ Principles of Data Science
+Course Learning Outcomes.
+At the end of the course, students are able to:
+1. Use data-driven solutions for domain specific related issues.
+2. Organize the steps that data scientists follow chronologically in a typical data science project.
+3. Develop a data product using open source tools.
+Synopsis of Course Content
+The course provides a breadth of knowledge, in terms of the what, when, who, where, why and how
+(8W 1H) in the field of data science. This foundation course is designed to help students discover
+useful insights from data of various domains. It incorporates the fundamental principles that underlie
+the algorithms, processes, methods, ethics, and data-analytic thinking in a data science life cycle. The
+role of data scientist, the knowledge and skills required is also presented. Diverse technologies,
+programming languages as well as tools in data science are discussed. Students will acquire practical
+knowledge through hands-on projects to come up with data science solutions and develop data
+products.
+Evaluation and Weightage
+Continuous Assessment 60%
+Final Examination 40%
+WQD7003__— Data Analytics
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Explain the basic concepts for various data analysis techniques
+2. Determine appropriate data analysis techniques to effectively generate useful information from
+data
+3. Design appropriate data analytics processes to solve real-world problems.
+Synopsis of Course Content
+This course aims to develop students’ ability to describe, explore and analyze data using suitable data
+analytics techniques.
+Evaluation and Weightage
+Continuous Assessment 60%
+Final Examination 40%
+
+### Page 79
+'WQD7004 Programming for Data Science
+Course Learning Outcomes
+At the end of this course, the students are able to:
+1. Solve problems in data science using various data structures and programming concepts.
+2. Mastering the program libraries and algorithms related to data science.
+3. Relate studies in the field of data science with the construction of appropriate applications.
+Synopsis of Course Content
+This course covers programming languages that are relevant to data science. The course provides
+students with the necessary programming skills for statistical analysis, exploration of datasets and
+predictions. These include understanding structures for data organization such as vector, list, matri
+and data frames; basic programming blocks such as operators, control structures, and subsettin
+using various libraries for data visualization; run prediction models using various models; and other
+algorithms.
+Evaluation and Weightage
+Continuous Assessment
+Final Examination
+50%
+50%
+'WQD7007 _— Big Data Management
+Course Learning Outcomes
+At the end of this course, the students are able to:
+1. Mastering the processes in the data pipeline.
+2. Explain database concepts and technologies for big data storage and retrieval
+3. Identify appropriate models, tools, and technologies to implement storage, search and retrieval
+systems for large-scale structured and unstructured information systems.
+Synopsis of Course Content
+This course prepares students to deal with large-scale collections of data as objects to be stored,
+searched over, selected, and transformed for use and reuse. It examines the underlying principles and
+technologies used to capture data, clean it, contextualize it, store it, and access it for a repurposed
+use. Data provenance is also examined to determine the trustworthiness of data.
+Evaluation and Weightage
+Continuous Assessment F 60%
+Final Examination i 40%
+Course Prerequisite: WQD7001
+WQD7012 Applied Machine Learning
+Course Learning Outcomes
+At the end of this course, students are able to:
+1. Explain the concepts and techniques for machine learning.
+2. Fine tune appropriate machine learning techniques for various datasets.
+3. Suggest practical solutions to common problems in machine learning.
+Synopsis of Course Content
+This course introduces fundamental concepts and techniques for machine leaming. It covers topics
+for both supervised and unsupervised learning approaches such as linear and logistic regression,
+neural network, decision trees and clustering etc.
+Evaluation and Weightage
+Continuous Assessment i 50%
+Final Examination s 50%
+Course Prerequisite: WQD7003
+o>
+
+### Page 80
+WQD7025 __— Data Science Research Project
+Course Learning Outcomes
+At the end of the course, the student are able to:
+1. Develop the data science research project in a form of report and presentation
+2. Prepare the data science research project plan and its results in an organized manner.
+3. Fine tune data science techniques to solve data science problems in the real world environment.
+Synopsis of Course Content
+The capstone project allows students to use public data or create data products by applying their
+knowledge in foundations, theory and methods of data science to address problems in industry and
+government. During the project, students engage in the entire process of solving a real-world data
+science project, from collecting and processing data ,to designing the best method to solve identified
+problems, to applying suitable analytic methods, and finally, to implementing a solution.
+Evaluation and Weightage
+Continuous Assessment : 100%
+Course prerequisite: At least passed 6 credits and accumulated from core courses, including
+wox7001
+WQD7005_— Data Mining
+Course Learning Outcomes
+At the end of this course, students are able to
+1. Mastering the concepts and techniques of data mining.
+2. Develop the appropriate solution for classification, association rules and clustering problems.
+3. Design practical solutions to streaming data.
+Synopsis of Course Content
+This course covers topics such as Data Warehouse, Pre-mining, Classification, Association Rules and
+Clustering Algorithms. It explains how to find pattems in a database and emphasises on hands-on
+experience of data mining tools.
+Evaluation and Weightage
+Continuous Assessment 50%
+Final Examination — : 50%
+WQD7008 __— Parallel and Distributed Computing
+Course Learning Outcomes
+At the end of this course, the students are able to:
+1. Analyse and appraise the basic principles and paradigms of parallel and distributed computing
+2. Solve issues and problems in the implementation of parallel and distributed systems.
+3. Integrate parallel and distributed system.
+Synopsis of Course Content
+This course focuses on the design and implementation of parallel and distributed processing systems.
+This course covers the fundamental concepts of distributed computing and introduces contemporary
+issues in big-data processing. This course emphasizes both the underlying principles and hands-on
+experience of data analytic tools.
+Evaluation and Weightage
+Continuous Assessment F 50%
+Final Examination i 50%
+
+### Page 81
+'WQD7009 __—Big Data Applications and Analytics
+Course Learning Outcomes
+At the end of this course, students are able to.
+4. Mastering the conceptual frameworks to identify the potential applications of big data in real-world
+scenarios,
+2. Design and implement data pipelines to process and integrate data from various sources.
+3. Explain the significance of big data in contemporary industry and technology.
+‘Synopsis of Course Content
+The course will cover Big data applications and analytics, Data Collection, Sampling and Pre-
+processing, Predictive Analysis, Descriptive analysis, Survival analysis, Social networks analysis, and
+Case study of Big data Applications.
+Evaluation and Weightage
+Continuous Assessment 70%
+Final Examination 30%
+'WQD7010 Network and Security
+Course Learning Outcomes
+At the end of the course, students are able to:
+4. Interpret the basic principles of cryptography, its framework and its application in network security.
+2. Mastering the new trend in network security, its application, and techniques to solve the network
+security problem
+3. Identify the problems in cryptography and explain the network security protocol.
+Synopsis of Course Content
+This course is designed to provide a practical survey of network security applications and standards.
+‘The emphasis on applications that are widely used on the internet and for corporate networks, and on
+standards, especially internet standards that have been widely deployed,
+Evaluation and Weightage
+Continuous Assessment 50%
+Final Examination 50%
+WQD7013 __ Statistics for Data Science
+Course Learning Outcomes
+At the end of the course, students are able to:
+4. Explain statistical concepts in solving problems in the field of data science
+2. Mastering descriptive statistics and inferential statistics in the field of data science
+3. Solving data science problems by applying statistical concepts learned using statistics-based
+software or programming
+Synopsis of Course Content
+The course will provide an opportunity for in-depth study of statistics techniques that are useful in data
+science. Topics relevant to the course include probability distribution, inference and bayesian statistics.
+Evaluation and Weightage
+Continuous Assessment 60%
+Final Examination 40%
+mm
+
+### Page 82
+‘WQF7007 Natural Language Processing
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Apply the Natural Language Processing (NLP) techniques in various domains.
+2. Design a Natural Language Processing (NLP) solution to resolve issues related to unstructured
+text.
+3. Develop an NLP application by integrating all processes in the NLP pipeline which are
+pre-processing, low level task and high level task.
+‘Synopsis of Course Content
+Natural language processing (NLP) is one of the most important areas in Artificial Intelligence (Al).
+This course covers the theory and practice of NLP through techniques for different levels which are
+pre-processing, low-level and high level. It also covers recent techniques and applications in NLP
+including Sentiment Analysis, Machine Translation, Topic Modeling and Named Entity Recognition.
+Evaluation and Weightage
+Continuous Assessment : 70%
+Final Examination 30%
+
+
+## Master of Cyber Security :: Programme Requirements
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 84-86
+
+### Page 84
+PROGRAMME REQUIREMENTS
+SS
+4. Programme Type
+The type of programme offered for the Master of Cyber Security is a programme consisting 10
+coursework which prepares students for the final capstone project which allows students to
+apply the knowledge they learned in the taught courses into real world applications
+2. Admission
+(2) Qualifications for Admission
+(i) Bachelor's degree with a GPA of not less than 3,00 in the field of Computer
+Science/information Technology/related fields;
+OR
+(ii) Bachelor's Degree with GPA (2.70 - 2.99) in the field of Computer
+Science/Information Technology/related fields and meet at least one (1) of the
+following criteria’
+¢ Graduated from the University of Malaya
+Have at least one (1) year of work experience in a related field
+‘¢ Produce publications in relevant fields
+‘ Scholarship recipient
+is an employee of a government agency.
+Pass the Faculty interview; or
+¢ passed the faculty's special assessment
+oR
+(iii) Specialist qualification from a recognized professional body;
+OR
+(iv) Other qualifications approved by the Senate from time to time.
+
+### Page 85
+(b)
+English Language Competency Requirements
+(i) Non-citizen applicants who obtained their degree from a university or institution of
+higher learning that does not use English as the medium of instruction for the degree J
+in question who wish to follow a degree program and/or to write their dissertation in
+English are required to meet the following requirements:
+‘* A minimum score of 550 for the paper-based test (PBT), a score of 213 for the
+‘computer-based test (CBT) or a score of 80 for the internet-based test (iBT)
+for the Test of English as a Foreign Language (TOEFL);
+‘* Minimum band 6.0 for the international English Language Testing System
+(IELTS) (Academic);
+cores according to the respective program standards if higher than (a) and (b);
+‘* For any program standard that places the TOEFL or IELTS (Academic) score
+lower than the University's minimum score, those programs must follow the
+minimum score that has been set by the University;
+‘* Minimum score of 57 Pearson Test of Academic English (PTE Academic);
+‘* Minimum grade C for English subject in General Certificate of Education (A-
+Level);
+‘¢ Minimum grade C in 82 First by Cambridge Assessment English;
+‘¢ Minimum grade C in C1 Advanced by Cambridge Assessment English;
+‘* Minimum grade C in C2 Proficiency by Cambridge Assessment English, or
+‘¢ Minimum band 4 in Malaysian University English Test (MUET).
+(i) Non-citizen applicants with the following backgrounds are exempt from the
+prescribed English language qualification requirements.
+‘* Comes from a country where English is the national language;
+‘* Possess an academic credential from an institution where English is the sole
+medium of instruction; or
+‘¢ Have studied in Malaysia and intend to pursue further education, subject to
+condition (b).
+Duration of Study
+‘The programme of study: two (2) semesters + one (1) special semester, to eight (8) semesters.
+Programme Structure
+- 2)
+The Master of Cyber Security Programme through coursework shall have a total of
+forty-three (43) credits.
+Through Coursework
+(i) The programme shall consist of two parts:
+(2) Part | comprises:
+(i) eight (8) core discipline courses, comprise of three or four credits
+courses; and
+(ii) two (2) elective courses, each four credits
+(b) Candidates may be imposed to enrol in other courses and obtain
+satisfactory results deemed necessary by the Faculty,
+Om
+
+### Page 86
+(3)
+(4)
+() Part Il consist of a ten (10) credits project and shall involve investigation
+and analysis of a real world case study, leading to the submission of a
+report.
+Details of courses offered shalll be of those approved by the Senate from time to time
+‘on the recommendation of the Faculty and shall be made known to the candidates at
+the start of each session.
+The list of Senate approved courses for the Master of Cyber Security Programme shall
+be as indicated in List 4
+
+
+## Master of Cyber Security :: Programme Objectives and Outcomes
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 87-88
+
+### Page 87
+PROGRAMME OBJECTIVES &
+OUTCOMES
+oe
+PROGRAMME EDUCATION OBJECTIVES (PEO)
+1. Graduates have advanced knowledge and practical skills, capable of using innovative
+techniques and digital technologies in the field of cyber security. ~’
+2. Graduates equipped with professional and ethical practices colaborate with organisations and "7A
+communities in developing innovative strategies to address present cyber threats.
+3. Graduates with a positive attitude, entrepreneurial mind set and sustainable practices
+progress toward lifelong learning for careers and professional development in cyber security.
+PROGRAMME LEARNING OUTCOMES
+No. Programme Learning Outcomes POs | Taxonomic Category
+1. [Critically analyse advanced knowledge and have capability to
+jurther develop related disciplines in the cyber security field. Pol K
+2. [Evaluate emerging scenarios and innovatively solve relevant issues
+through mastery of knowledge, analytical and critical skills
+3. Utilize various practical skills and digital technology methods of
+-yber security solutions to estimate, analyze, interpret and Po3 KP.
+lisseminate information
+Po2 K
+4. [Demonstrate abilities to communicate and work effectively with]
+t 4 ‘ Pos kp
+yeers, professional bodies and various communities
+5. Pesien innovative and effective solutions using digital technologies
+ind scientific and numeric skills POS PA
+6. Equip with leadership qualities and interpersonal proficiency te
+|demonstrate responsibility and autonomy in dynamic educational PO6 PA
+land organizational settings
+7 [Exhibit positive attitude and commitment to lifelong learning with
+entrepreneurial mind-set and professional development.
+PLO7 KA
+Total hours of student learning time for the entire program is 43 credits.
+f Vv
+A. WA Gist oF7 domains of learning outcomes in accordance with the MQF program. Please refer to the
+M attachment. Additional learning outcomes can be given if necessary)
+x
+) A
+Vv
+Ay”
+
+### Page 88
+y
+MATRIX OF PROGRAMME LEARNING
+EDUCATIONAL OBJECTIVE (PEO)
+OUTCOMES (PEO) AGAINST PROGRAMME
+Berets Programme Educational
+Outcomes (PLO) Objectives (PFO).
+peo1 | PEO2 | PEO3
+|pLoa x
+lpto2 x
+|pto 3 x
+|ptoa x
+ptos x
+ptos Xx
+|pLo7 x
+los x
+Reference notes:
+The Domain of the MQF in Programme Learning Outcomes program (PO)
+PO Domain
+PO1 Knowledge
+Po2 Practical Skills
+PO3 Social Skills and Responsibility
+Po4 Values, Attitudes and Professionalism
+POS ‘Communication, Leadership and Team Skills
+Pos Problem Solving and Scientific Skills
+PO7 Information Management and Life Long Learning Skills
+Pos Managerial and Entrepreneurial Skills
+Reference notes:
+Taxonomic Category
+v K Cognit
+gnitive
+AD A Atecive
+P Psychomotor
+A
+
+
+## Master of Cyber Security :: Course Plan
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 89-90
+
+### Page 89
++35.
+i? <
+COURSE PLAN
+INTAKE SEMESTER | 2025/2026
+‘Semester | | Semester Il | Semester Ill
+MASTER OF CYBER SECURITY Credits} 2925/2026 | 2025/2028 | 2025/2026
+Core Courses
+wox7001 | Research Methodology 3 v
+wae7001 | Cyber Security 3 v
+wae7o02 | Advanced Network Security 4 r
+Programming
+Network Technology and
+Wae7007 | Secunty -| v
+Cryptography and Information
+'WQE7003 Hiding 3 Vv
+WQE7004 Information Assurance 3 v
+WQE7005_| Advanced Digital Forensics 3 Vv
+W0C7020 | Advanced internet of Thing 3 v
+‘Cyber Security Research
+WAQE7008 | Eroject 10 v v
+Ween Cyber ‘Security Research 40 y v
+roject
+Elective Courses [Students are required to choose any 2 courses from the list
+below]
+WQE7008 | Wireless Networking and r ;
+Mobile Computing #
+WQE7011 | Advanced Computer 4 if
+Penetration and Defense
+wae7009 | Emerging Cyber Security 4 v
+Trends
+WQE7010 | Cloud Computing 4 4
+Note:
+*Students are only allowed to register for the WOE7006/WQE7023 (commencement of the 2024/2024
+academic year) Cyber Security Research Project after completing at least three (3) core discipline
+courses (including WOX7001)
+‘The courses that will be offered every semester are subject to change, depending on the availability of
+staff and the number of students registering.
+
+### Page 90
+COURSE PLAN
+Semester II| Semester ill | Semester | ‘we
+MASTER OF CYBER SECURITY Credits! 2995/2026 | 2025/2026 | 2026/2027
+y
+Core Courses
+wox7001_ | Research Methodology 3 v ~~
+wae7001 | Cyber Security 3 v A 4
+‘Advanced Network Security
+Wae7002_| Programming 4 v
+Network Technology and
+WAQE7007 | Security 3 a
+Cryptography and Information
+WaOE7003 | Hiding 3 y
+Wae7004_| Information Assurance g rr
+WQE7005_ | Advanced Digital Forensios 3 V
+Wo0C7020 | Advanced Internet of Thing 3 v
+waevo0s | Cyber Security Research 40 y y
+Project
+Cyber Security Research ;
+WQE7023. | Project 10 v v
+Elective Courses [Students are required to choose any 2 courses from the list
+below)
+WQE7008 | Wireless Networking and F i
+Mobile Computing ¥
+WQE7011_ | Advanced Computer 4 v
+Penetration and Defense
+WAQeE7009 | Emerging Cyber Security a v
+Trends
+WQE7010_ | Cloud Computing 4 ¥
+PW Note:
+*Students are only allowed to register for the WQE7006/W/QE7023 (commencement of the 2023/2024
+‘academic year) Cyber Security Research Project after completing at least three (3) core discipline
+A courses (including WOX7001)
+vw The courses that will be offered every semester are subject to change, depending on the availability of
+x staff and the number of students registering.
+va
+Ay”
+Vv
+A
+
+
+## Master of Cyber Security :: List of Courses and Contents
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 91-97
+
+### Page 91
+LIST OF COURSES &
+CONTENTS
+Se va’
+CORE COURSES
+Code Course Credits
+WOX7001 | Research Methodology
+WQE7001 | Cyber security
+WQE7002 | Advanced Network Security Programming
+WQE7003 | Cryptography and Information Hiding
+'WQE7004 | Information Assurance
+WQE7005 | Advanced Digital Forensics
+WQE7007 | Network Technology and Security
+WOC7020 | Advanced internet of Thing
+WQE7023_| Cyber Security Research Project
+eeevenoe
+ELECTIVE COURSES
+(NOTE: Students are required to choose any two (2) courses from the list below)
+Code Course Credits
+WQE7008 | Wireless Networking and Mobile Computing 4
+WQE7009 | Emerging Cyber Security Trends 4
+WQE7010 | Cloud Computing 4
+Wae7011_| Advanced Computer Penetration and Defense 4
+Note:
+* Students are only allowed to register for the WQE7023 Cyber Security Research Project after
+‘completing at least three (3) core discipline courses (Including WOX7001)
+Not all courses will be offered every semester; the actual courses offered will depend on the
+availability of staff and the number of students registering.
++35.
+i? <
+
+### Page 92
+‘WOX7001 Research Methodology
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Describe appropriate methodologies used in computer science and information technology
+research.
+2. Devise a plan to be carried out within a feasible duration for answering research problems and
+questions identified.
+3. Demonstrate attitude and character in line with professional and ethical codes in computer
+science and information technology research.
+Synopsis of Course Content
+This course gives on overview of the dimensions of research in computer science and information
+technology. Major considerations and tasks in conducting research in the areas such as review of
+literature, identify problem statement, formulate research questions and objectives, select an
+appropriate approach or method to the research, plan and manage the research, tools for research,
+data analysis, and writing and presentation strategies, will be discussed too.
+A
+Evaluation and Weightage
+Continuous Assessment
+Final Examination
+WQE7001 Cyber Security
+Course Learning Outcomes
+At the end of this course, students are able to:
+1. Understand cybersecurity operations, network principles, roles, and responsibilities as well as the
+related technologies, tools, regulations, and frameworks available.
+2. Integrate network monitoring tools to identify attacks against network protocols and services.
+3. Apply knowledge and skills to monitor, detect, investigate, analyse, and respond to security
+incidents.
+Synopsis of Course Content
+This course introduces the core security concepts and skills needed to monitor, detect, analyse, and
+respond to cybercrime, cyberespionage, insider threats, advanced persistent threats, regulatory
+requirements, and other cybersecurity issues facing organizations. It includes skills needed to practice
+cybersecurity operations knowledge in a controlled environment.
+Evaluation and Weightage
+Continuous Assessment 170%
+X Final Examination 30%
+we “a
+va
+ve WQE7002 Advanced Network Security Programming
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Determine the network security methods that can defence against cyber-attacks.
+2. Develop a secure network solution to mitigate the cyber threat.
+Ad Y 3. Synthesize ne’twork in terms of the exposure to potential threats, vulnerability and security.
+r
+A
+Vv
+
+### Page 93
+Synopsis of Course Content
+This course covers the networking and security challenges and the use of programming to defence
+against cyber-attacks and cyber threats. These include the procedures of network connection and
+endpoint protection. You will also learn how to assess a network's vulnerabilities and develop a secure r
+network solution with the help of Python scripting. Vv
+Evaluation and Weightage ~~’
+Continuous Assessment —: 60%
+Final Examination 240% J
+WQE7003 Cryptography and Information Hiding j
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Explain the principles and mechanism used in cryptography and information hiding
+2. Analyse the cryptographic and information hiding algorithms for their strengths and weaknesses.
+3. Evaluate the practical applications of cryptographic and information hiding mechanisms.
+‘Synopsis of Course Content
+This course consists of developing an understanding of cryptography, cryptanalysis, Symmetric and
+Asymmetric cryptographic algorithms (classic and modern algorithms), Introduction to Number Theory,
+Hash Functions, Message Authentication and Digital Signatures. This course also introduces the
+concepts and techniques used in information hiding which focuses mainly on watermarking and
+steganography. Topics includes spatial and transform domain embedding, media specific information
+hiding and attacks on watermarking and steganography.
+Evaluation and Weightage
+Continuous Assessment: 50%
+Final Examination : 50%
+WQE7004 Information Assurance
+Course Learning Outcomes
+At the end of this course, the students are able to:
+1. Analyze the challenges and solutions in Information Assurance involving the triad of people,
+processes and technologies.
+2. Evaluate security solutions to meet security needs for a meaningful society in accordance with the
+principles in information security.
+3. Ideate security solutions based on current challenges and issues in the topic of information
+security.
+Synopsis of Course Content
+This course covers and provides a practical view of security that involved the triad of people, policies
+and procedures and technology, which include: Information Assurance strategy, policy, concepts,
+Information Assurance planning, risk mitigation, Information Assurance detection and recovery
+process and application of Information Assurance in selected industries,
+
+### Page 94
++35.
+i? <
+Evaluation and Weightage
+Continuous Assessment 560%
+Final Examination 40%
+WQE7005 Advance Digital Forensics
+Course Learning Outcomes
+At the end of the course, the students are able to: ~”~
+1, Demonstrate the processes, methodologies, laws and regulations that have a significant "A
+relationship with the digital forensic domain.
+2. Plan all stages of digital evidence procedures (e.g., collection, recovery, preservation,
+identification, analysis and presentation).
+3. Relate the concept of digital forensics, anti-forensics, network and mobile forensics Find frequent
+item sets using FP-growth.
+Synopsis of Course Content
+The student will leam and understand the concept of digital forensics, computer crimes and criminals,
+acts and laws that have a significant relationship with digital forensic studies; international and local.
+Students will learn the process of collecting, preserving, recovering and analysing digital evidence. In
+order to present them in a proper presentation for non-Information Technology practitioners, students
+will practice the procedure of presenting digital evidence and building a cybercrime case. They also
+will learn the digital forensic methodologies, anti-forensics and network forensics as well as mobile
+forensics.
+Evaluation and Weightage
+Continuous Assessment 750%
+Final Examination 150%
+WQE7007 Network Technology and Security
+Course Learning Outcomes
+At the end of the course, students are able to’
+1. Identify the basic technologies that support the implementation of high-speed networks.
+2. Plan, configure, verify and integrate the implementation of various LAN and WAN routing
+protocols, and security
+3. Identify and solve the issues in the implementation of network and security aspects
+Synopsis of Course Content
+The course will provide knowledge and practical view of network technology. It includes technologies
+and advanced issues in IPv4 and IPv6, routing protocols, router, switches, network monitoring,
+high-speed networks and security in devices and routing,
+Evaluation and Weightage
+Continuous Assessment: 70%
+Final Examination 230%
+
+### Page 95
++35.
+i? <
+WE 7008 Wireless Networking and Mobile Computing
+Course Learning Outcomes
+At the end of this course, students are able to
+1. Explain the architecture and key technologies of Wireless Networks and Mobile Computing.
+2. Identify the challenges in the implementation of Wireless Networks and Mobile Computing
+3. Solve problems related to Wireless Networks and Mobile Computing communications.
+Synopsis of Course Content
+This course is designed to introduce to students the emerging issues related to Wireless Networks
+and Mobile Computing. This course will examine several aspects of Wireless Networks and Mobile
+Computing such as application areas related to Wireless Networks technologies, wireless network Wm
+‘components and application-level in Wireless Networks and Mobile Computing. This course also
+emphasises on solving problems related to Wireless Networks and Mobile Computing A
+communications.
+Evaluation and Weightage
+Continuous Assessment: 50%
+Final Examination : 50%
+WQE7009 Emerging Cyber Security Trends
+Course Learning Outcomes
+At the end of this course, students are able to:
+1. Identify the emerging trends in cybersecurity issues, attacks, threats and risks,
+2. Analyse the emerging approaches in mitigating and defending networks from the cyber-attacks,
+3. Apply the suitable approaches in analysing and synthesizing the emerging cyber-attacks and
+threats.
+Synopsis of Course Content
+This course covers the understanding of the emerging issues, attacks, threats and risk in cyber
+security. The topic is not limited to the existing issues, but also covers the possible issues in the near
+future. This include to analyse and understand how the latest technologies can be used to mitigate
+and defense the network from the cyber-attacks. This course extends the coverage by applying the
+suitable approaches in analysing and synthesizing the latest cyber-attacks and threats.
+Evaluation and Weightage
+Continuous Assessment 160%
+Final Examination 240%
+WQE7010 Cloud Computing
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Recognize the architecture and various basic concepts related to cloud computing technologies.
+2. Demonstrate cloud virtualization, cloud storage, data management and data visualization.
+3. Design cloud computing security using access control strategies.
+Synopsis of Course Content
+This course covers topics and technologies related to cloud computing various basic concepts and
+architecture models (such as laaS, PaaS, SaaS). It also discusses the important features of cloud
+computing such as cloud virtualization, cloud storage, clustering, data management and data
+Om
+
+### Page 96
+visualization. The theoretical knowledge and practical sessions will be applied to design cloud
+‘computing security using access control strategies.
+Evaluation and Weightage
+Continuous Assessment 60%
+Final Examination 240%
+WQE7011 Advanced Computer Penetration and Defense
+Course Learning Outcomes ~”~
+At the end of this course, the students are able to: A
+1. Identify the principles and techniques to hack and defend computer systems.
+2. Apply the concepts and techniques to hack and defend computer systems.
+3. Analyze the weaknesses in computer systems and their countermeasures.
+Synopsis of Course Content
+This course introduces the concepts and techniques used to hack and defend computer systems with
+a focus on ethical hacking. The contents of this course cover aspects of hacking such as network
+scanning, exploitation of vulnerabilities, gaining access to systems, and penetration testing.
+Evaluation and Weightage
+Continuous Assessment 170%
+Final Examination 30%
+woc7020 Advanced Internet of Things
+Course Learning Outcomes
+At the end of this course, students are able to:
+1. Explain the architecture and key technologies of internet of things.
+2. Identify the challenges in the implementation of internet of things.
+3. Solve problems related to internet of things in wireless communications.
+Synopsis of Course Content
+This course is designed to introduce to students the emerging issues related to internet of things. This
+course will examine several aspects of internet of things such as application areas related to internet
+of things technologies, real-time models, local sensors, network components and application-level
+components. This course also emphasises on solving problems related to wireless communications in
+developing and deploying internet of things.
+Evaluation and Weightage
+Continuous Assessment 50%
+Final Examination 250%
+WQE7023 Cyber Security Research Project
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Apply cyber security techniques to solve cyber security problems in real world environment
+2. Present the project plan and results professionally
+3. Write a project report
+
+### Page 97
+Synopsis of Course Content
+A research project is a medium-scale project to enable students to do research related to cyber
+security. Research projects allow students to use public data or create applications by applying
+knowledge in the basics, theories and scientific methods to solve problems related to cyber security.
+During the project, students will engage in the overall process of general research, starting with
+identifying problems, collecting and processing data, recommending solution methods, applying
+appropriate scientific methods and ending with implementing affordable solutions and evaluations.
+Evaluation and Weightage
+Continuous Assessment:100 %
+Final Examination: 0%
+Course Prerequisite: WOX7001
+
+
+## Master of Artificial Intelligence :: Programme Requirements
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 99-100
+
+### Page 99
+2,
+(J
+PROGRAMME REQUIREMENTS
+The type of programme offered for the Master of Artiféfal inteligence is a programme consisting
+of 10 courseworks that prepares students for the final capstone project which allows students
+to apply the knowledge they learned in the taught courses to real-world applications
+Admission
+University’s General Requirement Met the University's General Requirement
+Bachelor’s Degree Qualification Possess a Bachelor's Degree (Honours)
+Equivalent Qualification -
+Related Field Computer Sciences or Information
+Technology field
+Special Requirements ;
+University's General Entry Requirements:
+Possess a Bachelor's Degree with a CGPA of 3.00/4.00.
+OR
+Possess a Bachelor's Degree with a CGPA of 2.50 - 2.99 and;
+The applicant must fulfil at least one (1) of the following criteria:
+Universiti Malaya graduate or;
+Has at least one (1) year of work experience in related fields or;
+‘¢ Has produced publications in related fields or;
+A scholarship recipient or;
+A staff member of a government agency or;
+«Pass an interview conducted by the Faculty or;
+Pass a special evaluation by the Faculty.
+English Lanquage Competenc irements
+MUET B40
+IELTS 60
+TOEFL iBT (Center-based) 60
+TOEFL Essential (Online) 85
+Pearson Test of English (PTE) Academic
+B1 Preliminary, B2 First, C1 Advanced, C2 Proficiency
+Duration of Study
+The programme of study: two (2) semesters + one (1) special semester, to eight (8) semesters,
+Om
+
+### Page 100
+Programme Structure
+Ss
+The Master of Artificial Intelligence Programme through coursework shall have a total of forty-
+two (42) credits,
+(1)
+(2)
+(3)
+Through Coursework
+(i) The programme shalll consist of two parts:
+(2) Part | comprises:
+() Eight (8) core discipline courses, comprised of three or four credits
+courses; and
+(ii) two (2) elective courses, each three credits
+(b) Candidates may be imposed to enrol in other courses and obtain
+satisfactory results deemed necessary by the Faculty.
+(©) Part II consists of a ten (10) credit project and shall involve the
+investigation and analysis of a real-world case study, leading to the
+submission of a report.
+Details of courses offered shall be of those approved by the Senate from time to time
+on the recommendation of the Faculty and shall be made known to the candidates at
+the start of each session.
+The list of Senate-approved courses for the Master of Artificial Intelligence Programme
+shall be as indicated in List 1.
+C
+Ss
+(\
+
+
+## Master of Artificial Intelligence :: Programme Objectives and Outcomes
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 101-102
+
+### Page 101
+PROGRAMME EDUCATION OBJECTIVES (PEO)
+This programme will be able to
+PROGRAMME OBJECTIVES &
+OUTCOMES
+oe
+_awae
+Prepare graduates who can demonstrate the ability to apply artificial intelligence techniques
+theoretically and practically in a variety of situations.
+Develop graduates who can contribute their skills in the practical development of atificial
+intelligence for the well-being of society and the development of sustainability.
+Develop graduates who can demonstrate professional attitudes and ethics in producing science
+and technology solutions through innovative artificial intelligence.
+PROGRAMME LEARNING OUTCOMES (PLO)
+No.
+Programme Learning Outcomes PLOs Taxonomic
+Category
+Demonstrate the mastery of knowledge and thorough
+understanding of technological and scientific principles inthe | | PLO1 kK
+field of Artificial Inteligence.
+Recommend innovative solutions that are at the forefront of
+developments in Artificial Intelligence. Pua ul
+Evaluate Artificial Intelligence solutions and tools in terms of
+their usability, efficiency and effectiveness. bined &
+‘Communicate and interact effectively within @ group and
+with diverse stakeholders by publishing and presenting PLO4 PA
+technical materials in the fields of Artificial Intelligence.
+‘Apply various tools and techniques to design, analyze,
+interpret and validate knowledge related to the field of PLOS P
+Artificial Intelligence.
+Demonstrate leadership, teamwork, autonomy and
+responsibility in delivering services in Artificial PLOG PA
+Intelligence.
+Exhibit capabilities to extend knowledge through Iife-
+long learning with an entrepreneur's mindset in Artificial PLO? A
+Intelligence.
+Uphold professional and ethical practices in conducting
+research and delivering services in Artificial intelligence. Bios: iB
+
+### Page 102
+MATRIX OF MAPPING PLO TO PEO
+PEO
+eG PEO1 PEO2 PEO
+PLO1
+PLo2
+fe
+C
+PLO3
+PLO4
+PLOS
+PLOS
+PLOT
+PLos
+Reference notes:
+‘The Domain of the MQF in Programme Learning Outcomes program (PLO)
+PO Domain
+PLO1 — Knowledge
+PLO2 — Praotical Skis,
+PLO3 Social Skills and Responsibility
+PLO4 Values, Attitudes and Professionalism
+PLOS — Communication, Leadership and Team Skills
+PLO6 Problem Solving and Scientific Skills
+PLO7 Information Management and Life Long Learning Skills,
+PLOB8 — Managerial and Entrepreneurial Skills
+Reference notes:
+Taxonomic Category
+K Cognitive
+A Affective
+P Psychomotor
+fe
+(J
+
+
+## Master of Artificial Intelligence :: Course Plan
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 103-103
+
+### Page 103
+COURSE PLAN
+————-eo-—
+INTAKE SEMESTER | 2025/2026
+WwW
+Ss
+Research Project
+MASTER OF ARTIFICIAL credits | Semester! | Semester i
+INTELLIGENCE | 2026/2028 | 2028/2026
+Core Courses
+wox7001 | *Research Methodology 3 v y
+Advanced J
+WOA7O1S | Nachine Learning 2 4
+‘Artificial Intelligence ;
+WOF7002 Techniques 3 N
+Computer Vision and i
+WAF7006 | Image Processing Lj is
+Natural Language j
+war7007 | Paesing 4 y
+WOF7003 | intelligent Computation 4 v
+Data Analyfios in ;
+WOF7004 | Artficial Intelligence Ld ¥
+Data Privacy and
+WaF7005 } Artificial Intelligence 3 y
+Ethios
+war7o29 | Aftcial inteligence a 7 7
+Elective Courses [Students are required to choose an’
+\y two (2) courses from the list below]
+war7008 | Practical Deep Learning 3 v
+Explainable Arficial
+WAF7009 | inteligence (XAl) 2 N
+woa7o19 | Augmented Reality 3 v
+Robotics and r
+WOF7010 | Automation Es ‘
+War7011 | Cognitive Computing 3 v
+Note:
+*Students are only allowed to register for the WQF7023 Al Research Project after completing at least three (3)
+core discipline courses (including WOX7001)
+For Artificial intelligence Research Project (P1 and P2) must complete the project in consecutive semesters.
+Example
+P14 in Semester II and P2 in Special Semester
+‘© P1 in Special Semester and P2 in Semester |
+* P14 in Semester | and P2 in Semester II
+The courses that will be offered every semester are subject to change, depending on the availability of staff
+(J
+of students registering
+Om
+
+
+## Master of Artificial Intelligence :: List of Courses and Contents
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 104-111
+
+### Page 104
+LIST OF COURSES &
+CONTENTS
+ee es
+awtae
+KS
+CORE COURSES
+Code Course Credits
+WOXx7001 | Research Methodology 3
+WOA7015__| Advanced Machine Learning 3
+WQF7002 _| Artificial Intelligence Techniques 3
+WAF7006 | Computer Vision and Image Processing 3
+WaF7007 _| Natural Language Processing 4
+WQF7003 _| Intelligent Computation 4
+WQF7004 | Data Analytics in Artificial Intelligence 3
+WAF7005 _| Data Privacy and Artificial Intelligence Ethics 3
+WAF7023 _| Artificial Intelligence Research Project 10
+ELECTIVE COURSES
+(NOTE: Students are required to choose any two (2) courses from the list below)
+Code Course Credits
+WQF7008 | Practical Deep Learning 3
+WQF7009 | Explainable Artificial Intelligence (XA) 3
+WOA7019_ | Augmented Reality 3
+WAQF7010_ | Robotics and Automation 3
+WQF7011_| Cognitive Computing 3
+Note:
+*Students are only allowed to register for the WQF7023 Al Research Project after completing at least
+three (3) core discipline courses (including WOX7001)
+The courses that will be offered every semester are subject to change, depending on the availability of
+staff and the number of students registering.
+
+### Page 105
+S
+CJ
+WOX7001 _Research Methodology
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Describe appropriate methodologies used in computer science and information technology
+research,
+2. Devise a plan to be carried out within a feasible duration for answering research problems and
+questions identified.
+3. Demonstrate attitude and character in line with professional and ethical codes in computer
+science and information technology research.
+IW
+Synopsis of Course Content
+This course gives an overview of the dimensions of research in computer science and information
+technology. Major considerations and tasks in conducting research in the areas such as review of
+literature, identify problem statement, formulate research questions and objectives, select an
+appropriate approach or method to the research, plan and manage the research, tools for research,
+data analysis, and writing and presentation strategies, will be discussed too.
+Evaluation and Weightage
+Continuous Assessment: 100%
+Final Examination 10%
+WOA7015 Advanced Machine Learning
+Course Learning Outcomes
+At the end of this course, students are able to:
+1. Practice concepts and techniques for machine learning related to digital and numerical methods.
+Report the solution to machine learning problems by devising and listing the steps in machine
+learning applied to solve different types of problems
+3. Demonstrate skills and knowledge of machine learning by managing a machine learning project.
+Synopsis of Course Content
+This course introduces advanced concepts and techniques for machine learning. It covers topics such
+as linear and logistic regression, decision trees, neural networks, and support vector machines as
+well as reinforcement learning
+Evaluation and Weightage
+Continuous Assessment + 50%
+Final Examination 50%
+WQF7002 Artificial Intelligence Techniques
+Course Learning Outcomes
+At the end of the course, students are able to:
+Explain what constitutes Artificial Intelligence and identify systems with Artificial Intelligence
+elements.
+Apply basic principles of Artificial Intelligence in problem solving, inference, perception,
+knowledge representation, and machine learning.
+1.
+2. Analyse the applications of Artificial intelligence techniques in intelligent agents, expert systems,
+artificial neural networks, and other machine learning models.
+3.
+
+### Page 106
+This course introduces the core artificial intelligence concepts and skills that allow machines to mimic
+human intelligence. It contains a theory component about the concepts and principles that underlie
+modern Al algorithms, and a practice component to relate theoretical principles with practical
+implementation. Coverage includes knowledge representation, logic, inference, problem solving,
+search algorithms, game theory, perception, learning, planning, and agent design
+Synopsis of Course Content as
+Evaluation and Weightage
+Continuous Assessment — : 60%
+Final Examination 140%
+'WQF7006 Computer Vision and Image Processing
+Course Learning Outcomes
+At the end of this course, the students are able to:
+1. Evaluate suitable image processing techniques to solve artificial intelligence problems.
+2. Evaluate performances of image processing methods for a given artificial intelligence scenario.
+3. Design and develop image processing systems in the artificial intelligence domain
+Synopsis of Course Content
+This course explores image processing techniques in solving artificial intelligence problems. Image
+formation and image models are initial steps involved, It covers pixel and object level operations
+including histogram, edge, and segment. Image enhancement and restoration are compared. Image
+registration and image transform operations are included. Finally, image features and recognition
+processes are given. Deep learning approach for computer vision is included
+Evaluation and Weightage
+Continuous Assessment: 60%
+Final Examination 140%
+'WQF7007 Natural Language Processing
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Apply the Natural Language Processing (NLP) techniques in various domains.
+2. Design a Natural Language Processing (NLP) solution to resolve issues related to unstructured
+text.
+3. Develop an NLP application by integrating all processes in the NLP pipeline which are
+pre-processing, low level task and high level task,
+Synopsis of Course Content
+Natural language processing (NLP) is one of the most important areas in Artificial Intelligence (Al).
+This course covers the theory and practice of NLP through techniques for different levels which are
+pre-processing, low-level and high level. It also covers recent techniques and applications in NLP
+including Sentiment Analysis, Machine Translation, Topic Modeling and Named Entity Recognition,
+Evaluation and Weightage
+Continuous Assessment 170%
+Final Examination 130%
+a
+
+### Page 107
+WQF7003 Intelligent Computation
+C
+At the end of the course, students are able to:
+1. Explain how mathematical theories help in solving Al problems.
+2. Solve Al problems with formal reasoning.
+3. Combine mathematical techniques in solving artificial intelligence problems.
+Synopsis of Course Content
+This course covers fundamental mathematical theories that support the development of artificial
+intelligence. Topics covered include logic and reasoning, linear algebra, graph theory and search
+algorithms, and probability theory.
+This course finds relation with other courses in the program, such as: Advanced Machine Learning
+where linear algebra, graph theory and search algorithms are used heavily; Computer Vision and
+Image Processing where linear algebra and probability theory finds their applications; and Natural
+Language Processing which has relation with graph theory and search algorithms, as well as logic and
+reasoning. The content of this course is also the fundamental of courses like Practical Deep Learning
+and Artificial Intelligence Techniques.
+Evaluation and Weightage
+Continuous Assessment: 50%
+Final Examination 150%
+WQF7004 Data Analytics in Artificial Intelligence
+Course Learning Outcomes
+At the end of this course, students are able to:
+1. Explain the basic concepts of data analytics in Artificial Intelligence in various domains.
+2. Design domain-based data analytic pipeline to solve real world Artificial Intelligence problems,
+3. Apply suitable data analytics techniques to solve real world problems for Artificial intelligence.
+Synopsis of Course Content
+This course aims to develop students’ ability to describe, explore and analyse various types of data
+(tabular, text and images) using suitable data analytics techniques and do predictive modelling by
+using different Machine Learning techniques.
+Evaluation and Weightage
+Continuous Assessment: 60%
+Final Examination 240%
+fe
+(J
+
+### Page 108
+WQF7005 Data Privacy and Artificial Intelligence Ethics
+Course Learning Outcomes
+At the end of this course, the students are able to:
+1, Assess the importance of data privacy and ethical concepts in the development of Artificial
+Intelligence system.
+2. Check current smart systems and technologies that are less concerned with ethical issues and
+data privacy.
+3. Design Artificial Intelligence technology to be more responsible and in line with the needs of
+industry and society
+_awae
+‘Synopsis of Course Content
+The course describes the concepts and philosophy of data privacy and ethics in Artificial Intelligence
+technologies. All strategies for developing a more responsible Artificial Intelligence system will be
+explained in more detail. The course also analyse and critique issues of data privacy violations or
+unethical values in current smart systems and technologies
+Evaluation and Weightage
+Continuous Assessment 170%
+Final Examination 230%
+WQF7023 —_— Artificial Intelligence Research Project
+Course Learning Outcomes
+At the end of this course, students are able to:
+1. Design solution using artificial intelligence techniques for real world problems.
+2. Develop Artificial Intelligence-based solution formulated on project objectives,
+3. Explain solution in oral and written presentation related to artificial intelligence research.
+‘Synopsis of Course Content
+A research project is a medium-scale project to enable students to do research related to artificial
+intelligence. Research projects allow students to use actual data from industry partners or public data
+to create applications by applying knowledge in the basic, theories and scientific methods to solve
+problems related to artificial intelligence. During the project, students will engage in the overall
+process of general research, starting with identifying problems, collecting and processing data,
+recommending solution methods, applying appropriate scientific methods and ending with
+implementing affordable solutions and evaluations. At the end of the course, students are required to
+submit a project report and perform a project presentation.
+Evaluation and Weightage
+Continuous Assessment: 100%
+Final Examination 20%
+Course Prerequisite: WOX7001
+fe
+(J
+
+### Page 109
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Unifies the knowledge on the fundamentals and architectures of deep learning, and the need for
+parallel and distributed computing for deep learning.
+2. Integrate and develop the requirements for cloud computing infrastructure, GPU and relevant
+software as well as tools for setting up, modelling, debugging and serving of deep learning
+projects.
+3. Practice the knowledge and skills to design deep learning based solutions.
+Synopsis of Course Content
+This course is closely linked with the Advanced Machine Learning course which is a pre-requisite for
+this course. It reinforces the knowledge on the fundamental concepts related to deep leaming (such
+as different deep learning architectures) and introduces practical techniques to get started on Artificial
+Intelligence projects and develop an industry portfolio. Specifically, it will provide the necessary
+knowledge and skills on how to design a deep learning production system end-to-end: project
+scoping, data needs, modelling strategies, and system deployment requirements.
+WaQF7008 Practical Deep Learning OC)
+Evaluation and Weightage
+Continuous Assessment: 60%
+Final Examination 140%
+Course Prereq
+WaQF7009 Explainable Artificial Intelligence (XAI)
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Categorize the concepts of Explainable Artificial Intelligence (Al) and the current techniques for
+generating explanations from black-box machine learning methods.
+2. Design the Explainable Al methods.
+3. Develop the ability to critically assess the state-of-the-art of Explainable Al methods.
+Synopsis of Course Content
+This course gives an introduction to Explainable Al (XA\), providing an overview of relevant concepts
+such as interpretability, transparency and black-box machine learning methods. The course provides
+an overview of state-of-the-art methods for generating explanations, and touches upon issues related
+to decision-support, human interaction with Al/intelligent systems and their evaluation. In summary,
+the Explainable Al course covers the following topics: definitions and concepts such as black-box
+models, transparency, interpretable machine learning and explanations, explainable Al models,
+methods for Explainable Al, applications and examples.
+Evaluation and Weightage
+Continuous Assessment —_: 60%
+Final Examination 140%
+fe
+(J
+
+### Page 110
+Woa7019 Augmented Reality OC)
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Describe the technologies related to Augmented Reality.
+2. Apply the related new technologies in the design of augmented reality applications.
+3. Develop interactive augmented reality applications for both PC based and mobile devices using a
+variety of input devices.
+(\
+Synopsis of Course Content
+This course is designed to introduce students with knowledge related to augmented reality concepts
+and technology. This is followed with a discussion on how knowledge about human sensory systems
+can facilitate in designing ergonomic augmented reality devices that match human perceptual
+capabilities. Students are then trained to develop an augmented application using a suitable
+programming language and 3D software. Towards the end of the course, there will be discussions on
+several examples of augmented reality applications with emphasis on the contributions of the
+augmented reality technology and future direction of this technology.
+Evaluation and Weightage
+Continuous Assessment: 70%
+Final Examination 130%
+WQF7010 Robotics and Automation
+Course Learning Outcomes
+At the end of the course, students are able to:
+1. Design robotic and automation systems using parts like sensors, controllers and actuators.
+2. Infer patterns from data collected.
+3, Evaluate robotic and automation systems for optimum performance in various applications.
+Synopsis of Course Content
+This course focuses on developing robotic and automation systems by integrating components such
+as sensors, controllers, motors and actuators. Students apply data acquisition methods, control
+methods and also program robot sensing, connectivity, mobility and manipulation to achieve
+automation. Additionally, students can apply artificial intelligence techniques to analyse collected data
+for informed decision making.
+Evaluation and Weightage
+Continuous Assessment: 70%
+Final Examination 230%
+fe
+(J
+
+### Page 111
+warF7011 Cognitive Computing
+Course Learning Outcomes as
+At the end of the course, students are able to:
+1. Assess the relationship between cognitive computing systems, artificial intelligence and and
+human interaction.
+2. Specify requirements and techniques for designing cognitive computing systems.
+3. Develop cognitive computing systems as a solution for artificial intelligence applications.
+Synopsis of Course Content
+The student will learn and understand the concept of cognitive computing systems and its relations
+with artificial intelligence and big data, Students will also leam the requirements and techniques such
+as the characteristics, components and architecture needed to design cognitive computing system
+applications powered by multiple Al technologies encompassing machine learning, reasoning, natural
+language processing, speech recognition and vision (object recognition), human-computer interaction,
+dialog and narrative generation. In addition, students will also evaluate how such systems can be
+used to achieve human-like behaviors that improve the performance of human-machine interactions in
+various domains
+Evaluation and Weightage
+Continuous Assessment + 70%
+Final Examination 130%
+
+
+## Master of Computer Science (By Research) :: Programme Requirements
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 113-113
+
+### Page 113
+PROGRAMME REQUIREMENTS
+oS
+4. Programme Type
+The type of programme offered for the Master of Computer Science by Research is one hundred
+per cent (100%) research leading to the submission of a dissertation
+2. Entry Requirements
+For admission into the Master of Computer Science programme, applicants must have at least:
+* A Bachelor's degree with Honours or a comparable degree in Computer Science or
+Information Technology; or
+© Other qualifications approved by the University Senate.
+‘* Priority is given to applicants with a CGPA of 3.0 and above or equivalent.
+Intemational applicants are required to have
+© At least IELTS Band 6 (Academic) or TOEFL score of 550 (paper-based) / 213
+(computer-based) / 80 (Internet-based) if their first degree is from a university where
+English is not the medium of instruction.
+3. Duration of Study
+The programme of study: two (2) to eight (8) semesters.
+4. Programme Structure
+(i) This programme shall consist of one hundred percent (100%) research work leading
+to the submission of a dissertation which format shall be stipulated as in Part VIl,
+University of Malaya Regulations (Master's Degree) 2019
+(i) Attend and pass a Research Methodology Course — WOX7001 (three (3) credits) not
+later than the second semester of candidature
+(ii) Candidates may be imposed to enroll in other courses and obtain satisfactory results
+deemed necessary by the Faculty.
+5. Determination of Research Area
+Determining the research area shall be done upon the candidate’s admission into the
+programme.
+
+
+## Master of Computer Science (By Research) :: Learning Objectives and Outcomes
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 114-115
+
+### Page 114
+PROGRAMME LEARNING
+OBJECTIVES & OUTCOMES
+SS
+PROGRAMME EDUCATIONAL OBJECTIVES (PEO)
+4. To produce researchers who can contribute to the development and knowledge of computer science
+2. To produce professionals in computer science research
+3. To equip graduates with technical and soft skills
+PROGRAMME LEARNING OUTCOMES (PLO)
+Taxonomic
+No. Programme Learning Outcomes PLOs Gubecte
+1. [Apply and integrate knowledge on the latest research issues |p) Gy 3S
+in computer science and produce state-of-the-art research.
+2. [Evaluate and analyse computing solutions in terms of re Pp
+usability, efficiency and effectiveness
+3. [Produce computing solutions and use appropriate tools to
+lanalyse the performance of such solutions in meeting the PLOS Pp
+Ineeds of society
+4 [Apply existing research techniques to acquire, interpretand |p, og =
+Jdevelop knowledge in computing
+5._[Communicate and work in groups effectively PLOS AP,
+6. Provides, publishes and presents technical materials to a — Pp
+lwice audience
+7. [Demonstrate consistent behaviour with a code of ethics and
+professional responsibility to acquire information and apply PLOT A
+knowledge at alll times
+(List of 11 domains of learning outcomes in accordance with the MF program.)
+
+### Page 115
+MATRIX OF MAPPING PLO TO PEO
+66 = PEO1 PEO2 PEO3
+PLO1 x |
+x
+x
+x
+PLOS x x
+PLOG x
+PLOT
+Reference notes:
+The Domain of the MQF in Programme Learning Outcomes program (PLO)
+PO Domain
+PLO1 —_ Knowledge and Understanding
+PLO2 Numeracy Skills
+PLO3 Practical Skills, Digital Skills
+PLO4 = Cognitive Skills
+PLOS _ Interpersonal Skills, Communication Skills
+PLO6 _ Leadership, Autonomy and Responsibility
+PLO7 Ethics and Professionalism
+Reference notes:
+Taxonomic Category
+K Cognitive
+A Affective
+P Psychomotor
+
+
+## Master of Computer Science (By Research) :: Candidature Requirements
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 116-116
+
+### Page 116
+CANDIDATURE
+REQUIREMENTS
+Master of Computer Science (Master by Research)
+No Requirement
+1. | Fulfil the minimum candidature of two (2) semesters
+2. _ | Fulfil the University language requirement-Bahasa Malaysia (International Candidate)
+Fulfil the University language requirement-English Language (International Candidate)
+Research Methodology Course
+Present research proposal at Proposal Defence
+Present research progress at Candidature Defence
+Fulfil the publication requirement according to the oriteria set in the publication guidelines
+before graduation.
+‘Show proof of acceptance for publication of at least one (1) arficle in journals indexed by
+g, _ | Thomson Reuters Web of Science (WOS) (according to the criteria set in the publication
+guidelines), before graduation “and fulfil the residential requirement for at least one (1)
+semester
+~ Jolla] o
+The candidates must fulfil the following publication requirements before the Examination
+Committee (Board) meeting:
+Publication Requirements
+‘* Masters Degree Candidate pursuing a programme in the field of Science must show proof of
+acceptance of publication for at least one (1) paper in ISI (WoS) Journals before a Committee of
+Examiners meeting
+
+
+## Master of Computer Science (By Research) :: Graduate on Time (GOT) Schedule
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 117-117
+
+### Page 117
+GRADUATE ON TIME (G0T)
+SCHEDULE
+-——_ Se
+‘Semester Activities Output/Milestone ‘Comments
+1 © Meet the supervisor
+Attend Research Methodology Course
+'* Attend Bahasa Melayu course"
+Topic Confirmation
+'* Familiarisation with and use of EndNote, Tumitin, | 6 Completed Research Methodology course
+‘editing software, data analysis and research tools.
+‘© Fufflment of language requirements
+© Conduct Literature Review
+‘© Presented research proposal
+'* Proposal Defence preparation and drafting (writing
+‘proposal and prepare slides)
+‘© Proposal Defence
+'* Prepare for Publication 1
+‘© Ethics Approval (f applicable)
+Progress Report Submission
+2 ‘© Proposal Refinement based on feedback
+'* Expand research proposal to drafts of chapters 1
+283 ‘© Completed outine of dissertation
+# Conduct pilot study’ planning & setting up of ‘© Submission of Publication 1
+‘experiment start data collection ‘© Completed Candidature Defence
+© Start Development
+© Begin data analysis
+‘© Propare and present Candidature Defence
+© Submit Publication 1
+Progress Report Submission
+3 # Finalsed all chapters
+# Review with supervisors) © Completed all chapters
+Paper Publication outcome (Correct paper and . -*
+pores merr Submission of dissertation
+© Dissertation Submission
+'* Progress Report Submission
+* ‘© Dissertation correction (based on internal and '® Outcome of Committ
+‘external examiner)
+of Examiners
+© Received Senate letter.
+© Journal acceptance
+Notes:
+Monitoring Panel
+1, Chairman & 1 member who is an expert in the field and a supervisor. A fourth member is allowed to be appointed if necessary.
+2. The same panel should follow through with the proposal presentation and Candidature Defense.
+3. tis strongly recommended that one member be appointed as an internal examiner.
+4. The primary responsibilities of the panel should include the following:
+- Advise the student to improve the research proposal,
+- Monitor the progress of the student
+- Improve the research plan.
+* Applicable to all international candidates.
+** Applicable to international candidates writing their dissertation in languages other than English.
+
+
+## Master of Computer Science (By Research) :: Research Methodology / Course Contents
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 118-118
+
+### Page 118
+LIST OF COURSES &
+CONTENTS
+oo Ss +2
+WOX7001 —_- Research Methodology
+Course Learning Outcomes
+‘At the end of the course, students are able to
+1. Describe appropriate methodologies used in computer science and information technology
+research.
+2. Devise a pan to be carried out within a feasible duration for answering research problems and
+questions identified.
+3. Demonstrate attitude and character in line with professional and ethical codes in computer science
+and information technology research
+‘Synopsis of Course Content
+This course gives an overview of the dimensions of research in computer science and information
+technology. Major considerations and tasks in conducting research in the areas such as review of
+literature, identify problem statements, formulate research questions and objectives, select an
+appropriate approach or method to the research, plan and manage the research, tools for research,
+data analysis, and writing and presentation strategies, will be discussed too.
+Evaluation and Weightage
+Continuous Assessment 100%
+Final Examination 1 0%
+WOX7002 _ Dissertation
+‘Synopsis of Course Content
+The dissertation is the core of the Master of Computer Science by Research, where students conduct
+independent research under supervision in a chosen area of computer soience. Through milestones
+such as proposal defence, candidature defence, and thesis submission, students demonstrate theit
+ability to solve research problems, apply suitable methodologies, and contribute original findings.
+Emphasis is placed on scholarly writing, publication, and the development of critical thinking and
+research skills, preparing graduates for doctoral studies or research-oriented careers.
+Evaluation
+Proposal Defence
+Candidature Defence
+Dissertation Report
+
+
+## Doctor of Philosophy :: Advanced Research Methods Course Content
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 120-120
+
+### Page 120
+COURSE CONTENT
+‘WVX8001 Advanced Research Methods in Computer Science and Information
+Technology
+Course Learning Outcomes
+At the end of the course, students are able to:
+14. Describe the epistemological issues underlying research in computer science and information
+technology.
+2. Explain the approaches and issues involved in conducting research in computer science and
+information technology.
+3. Employ appropriate advanced research designs when conducting computer science and information
+technology research
+4. Apply appropriate statistical techniques when conducting computer science and information
+technology research.
+5. Prepare a viable doctoral level proposal for a research degree in computer science and information
+technology.
+‘Synopsis of Course Content
+This course covers the scope, types, basic skills and methodological aspects of computer science and
+information technology research. Topics include design of experimental research, survey research,
+grounded theory and phenomenological research, case study, action research, role of statistics in
+research and art of preparing a research proposal
+Evaluation and Weightage
+Continuous Assessment : 100%
+Final Examination : 0%
+wvx8002 —- Thesis.
+
+
+## Doctor of Philosophy :: Programme Education Objectives
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 121-121
+
+### Page 121
+PROGRAMME EDUCATION
+OBJETIVES
+oe
+PEO 1:
+Foster innovation of new ideas, methods and techniques in relevant research fields
+PEO 2:
+Lead research and establish a career as a skilled researcher and/or practitioner
+PEO 3.
+Disseminate research output and provide expert advice through various mechanisms in an
+ethical and professional manner
+
+
+## Doctor of Philosophy :: Learning Outcomes
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 122-122
+
+### Page 122
+LEARNING OUTCOMES
+S56
+Synthesis and contribute knowledge in the respective research field.
+Adapt appropriate practical skills and research methodologies leading to innovative
+research.
+Provide expert advice to relevant stakeholders based on respective research output.
+Conduct research independently and adhere to legal, ethical and/or professional codes of
+practice.
+Display leadership qualities through effective communication and collaboration with peers
+and stakeholders.
+Address issues in the field of research critically by using appropriate problem solving and/or
+scientific skills
+
+
+## Doctor of Philosophy :: Candidature Requirements
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 123-123
+
+### Page 123
+CANDIDATURE
+REQUIREMENTS
+Doctor of Philosophy Degree:
+No Requirement
+1. _ | Fulfil the minimum candidature duration of 4 semesters.
+2, _| Fulfthe University language requirement (Bahasa Malaysia) not later than the
+"| second (2"4) semester of candidature.
+Fulfil the residential requirement of 6 months
+Candidates are considered have fulfiled the residential requirement if they have
+3. | completed requirements 4, 5, 6 and 7 and including the following:
+(a) Face-to-face consultation with supervisor(s) as imposed by the faculty; and/or
+(b) Participation in any faculty activities as required by the faculty.
+‘Attend at least 3 credits of Research Methodology Course not later than the second
+4, | (2nd) semester of candidature.
+Present your research proposal at Proposal Defence not later than the second (2nd)
+5. | semester of candidature.
+Present your research progress at Candidature Defence not later than the fifth (6th)
+6. | semester of candidature.
+Present your research progress at Thesis Seminar before the submission of thesis
+7. | for examination.
+The candidates must fulfil the following publication requirement before the Viva-Voce
+and the Examination Committee (Board) meeting:
+8. _ | Publication Requirements
+© Timing ~ Publications must be within the candidature of the candidate.
+© Topics of Publications — Publications must be related and conform to the
+candidate's research in his/her thesis.
+* Affiation — Publications must carry the affiliation of the department and/or
+faculty where the candidate is registered.
+
+
+## Doctor of Philosophy :: Proposed Graduate on Time (GOT) Schedule
+
+- scope_label: postgraduate
+- source_doc: Complete Handbook
+- pages: 124-124
+
+### Page 124
+PROPOSED GRADUATE ON
+TIME (GOT) SCHEDULE
+oe
+Semester Activities ‘Outputiilestone
+7 ‘= Met supervisor) ‘Completed Research Methodology
+‘© Tope Confirmation couse
+‘¢ Attend Research Methodology Course ‘© Fulfmert of language requirements
+‘tend Bahasa Melayu course” Preserted research proposal
+‘© Familiarization with and use of EndNote, Turnitin, editing sofware, data analysis, Submit Progress report
+‘and research tools
+'¢ Conduct Literature Review
+‘* Proposal Defence preparation and drafting (wating proposal and preparing slides)
+‘© Proposal Defence
+‘¢ Prepare for Publication 1
+‘© Ethics Approval if applicable)
+‘© Progress report submission
+z ‘> Refine proposal based on feedback = Workable prototype existing
+‘© Conduct pot study / pian and set up experiment /start data collection methods
+‘© Stat development ‘© Generate preliminary resuits
+‘8 Reproduce existing methods ‘© Suamission of Publication 1 (review
+‘Begin data analysis paper / experimertal design)
+‘© Prepare for Candidature Defence ‘© Submit Progress report
+‘© Submit Publication 1
+Progress report submission
+z ‘© Candidalure Defence preparation and drafing (wiling Candidalure Defence = Completed Canaidature Defence
+document and preparing sides) ‘© Submit Progress report
+‘* Candidature Defence
+‘© Paper 1 publication outcome (Correct paper and submit if needed)
+Discussion preliminary results with supervior(s)
+Progress report submission
+a ‘© Experimentation andlor data analysis = Submission of Publication 2
+‘¢ _Thesis wnte-up (Chapter 1,2 3) © Completed drafts of thee chapters
+Review wih eupenisor) ‘= Submit Progress report
+Prepare and submit for Publication 2
+Progress report submission
+G ‘Thesis wite-up (complete remaining chapters) ‘Completed hess craft
+‘© Presentation of Thesis Seminar ‘© Presented Thesis Seminar
+‘© Review with supervisors) ‘© Submit Progress report
+‘© Paper 2 publication outcome (Correct paper and submt if needed)
+‘© Progress report submission
+G = Finalize and submit thesis = Submission of esis
+‘© Review with supervisors) = Wwvavooe
+‘© Prepare for viva voce Outcome of Committee of Examiners
+‘© Thesis correction and final thesis submission (based on internal and external Receive serate letter
+examiners)
+‘© Journal acceptance
+“Applicable to all international candidates.