Course Weeks

This course consists of 12 weeks covering the theory and practice of agentic AI systems.

Progress Overview

12/12 Weeks Complete

All Weeks

Week 1: Introduction to Agentic AI

Agent definitions, ReAct paradigm, autonomous systems overview

Slides First Agent

Week 2: LLM Foundations for Agents

Chain-of-Thought, Tree-of-Thoughts, prompting strategies

Slides Prompting Strategies

Week 3: Tool Use and Function Calling

MCP protocol, OpenAI/Anthropic APIs, tool design

Slides MCP Tool Implementation Function Calling Comparison

Week 4: Planning and Reasoning

Reflexion, LATS, hierarchical planning, memory

Slides Reflexion Implementation

Week 5: Multi-Agent Architectures

Communication topologies, AutoGen, MetaGPT, ChatDev

Slides Message Passing Coordination Demo

Week 6: Agent Frameworks

LangGraph, CrewAI, framework comparison and selection

Slides LangGraph Agent

Week 7: Advanced RAG

Self-RAG, CRAG, RAPTOR, agentic retrieval

Slides Self-RAG Implementation

Week 8: GraphRAG and Knowledge

From vector search to knowledge graphs for structured retrieval

Slides GraphRAG Implementation

Week 9: Hallucination Prevention

Verification, grounding, and factuality for trustworthy agents

Slides Verification Pipeline

Week 10: Agent Evaluation

Benchmarks, metrics, and assessment for rigorous agent testing

Slides Benchmarking Suite

Week 11: Domain Applications

Code, finance, and healthcare agents with domain-specific constraints

Slides Code Generation Agent

Week 12: Research Frontiers

Open problems, future directions, and cutting-edge research

Slides Generative Agents Demo

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Table of contents

• Week 1: Introduction to Agentic AI
• Week 2: LLM Foundations for Agents
• Week 3: Tool Use and Function Calling
• Week 4: Planning and Reasoning
• Week 5: Multi-Agent Architectures
• Week 6: Agent Frameworks
• Week 7: Advanced RAG
• Week 8: GraphRAG and Knowledge
• Week 9: Hallucination Prevention
• Week 10: Agent Evaluation
• Week 11: Domain Applications
• Week 12: Research Frontiers