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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
-
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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)
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-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
-
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-- 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
-
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-- 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
-
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-- 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
-
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-
-### 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
-
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-- 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
-
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-- 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.