Comprehensive curriculum from Fundamentals to GenAI & Agentic AI
Complete Zero to Hero journey. CNNs, RNNs, LSTMs, Transformers, GANs, and Diffusion Models. Featuring rigorous "Paper & Pain" math and interactive visualizations.
Comprehensive single-page deep learning reference. Detailed theory, math derivations, and hands-on code for every major topic.
LLMs, Context Engineering, RAG, Vector DBs, AI Agents, LangChain, MCP, A2A, AG-UI and Production deployment. Based on the AI Engineering Guidebook 2025.
From essential syntax to advanced production engineering. Master OOP, decorators, asynchronous programming, NumPy, and performance optimization.
CI/CD pipelines, Docker, Kubernetes, Security, and MLOps on Azure. From Zero to Production with YAML pipelines and IaC.
The foundation. Regression, Classification, Clustering, SVMs, Decision Trees, and Ensembles. Master Scikit-Learn.
Hands-on laboratory for datasets, experimental scripts, and practical ML applications.
Calculus, Linear Algebra, and Probability. The engine room of AI. Derivatives, Matrix Operations, and Eigenvalues.
Descriptive and Inferential Statistics. Hypothesis testing, Distributions, P-values, and Bayesian concepts.
Data cleaning, transformation, scaling, encoding, and selection. The art of preparing data for models.
Matplotlib, Seaborn, Plotly. Communicating insights effectively through beautiful charts and dashboards.
Mastering LLMs. Zero-shot, Few-shot, Chain-of-Thought, and advanced prompting strategies for GPT-4/Claude.
In-depth specialized course for Anthropic's Claude. Learn system prompts, complex tool use, chaining, and advanced safety techniques.