GenAI Course 2025

A comprehensive course on Generative AI—from foundational concepts to advanced implementations with RAG, agents, and workflows.

YouTube Playlist

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📚 Course Materials

1. Introduction

Lectures:

• Course Introduction (03:33)
• How GenAI Works? (26:38)

Demo:

• First Interaction with the LLM (20:53)
• Your First Chatbot App (06:10)

Slides: slides/1. Intro

Code: src/1. Intro

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2. Tokenization, Embeddings, and Transformers

Lectures:

• Tokenization (6:14)
• Embeddings (23:54)
• Transformers - attention (49:36)
• Transformers - Multi-Layer Perceptron (15:38)
• Transformers - Prediction (13:55)

Demo:

• Embeddings (17:38)

Slides: slides/2. Transformers

Code: src/2. Models

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3. Retrieval Augmented Generation (RAG)

Lectures:

• RAG - foundations (21:41)
• RAG - evaluation (17:59)

Demo:

• Minimal RAG (20:41)
• Chunking (9:14)
• Vector Stores (16:37)
• Document Loaders (19:54)
• Advanced RAG Techniques (32:35)
• RAG Evaluation with RAGAS (21:27)
• GraphRAG with Neo4j - Part 1 (22:43)
• GraphRAG with Neo4j - Part 2 (6:17)
• GraphRAG with Neo4j - Part 3 (11:53)

Slides: slides/3. Retrieval Augmented Generation

Code: src/3. Retrieval Augmented Generation

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4. Graphs

Lectures:

• Chains and Graphs (37:15)

Demo:

• Basig Graph (13:34)
• Parallel Processing (13:10)
• Map Reduce (09:53)

Slides: slides/4. Graphs

Code: src/4. Graphs

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5. Tools and Agents

Lectures:

• Tools and Agents (21:41)
• Functions, LLMs, and Agents - a wider picture (16:54)
• Multi-Agent Architectures (18:57)
• Agentic AI Evaluation (17:21)

Demo:

• OpenAI Function Calling (10:22)
• LangChain Tools (18:08)
• LangGraph ReAct (20:42)
• Complex Agent - Part 1 (12:26)
• Complex Agent - Part 2 (12:19)
• Multi-Agent Systems with LangGraph (14:32)
• Research Assistan (18:43)
• Multi-Agents Systems with A2A (18:15)

Slides: slides/5. Tools and Agents

Code: src/5. Tools and Agents

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6. Model Context Protocol (MCP)

Lectures:

• Model Context Protocol - Introduction (35:50)
• MCP vs Agentic AI (8:40)

Demo:

• MCP (10:42)

Slides: slides/6. MCP

Code: src/6. MCP

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🚀 Getting Started

Prerequisites

• Python 3.10+ (3.11+ recommended)
• uv package manager

Installation

1. Install uv:

curl -LsSf https://astral.sh/uv/install.sh | sh

2. Clone the repository:

git clone https://github.com/wodecki/TEG_2025.git
cd TEG_2025

3. Install dependencies:

uv sync

4. Set up API keys: Create .env files in relevant module directories:

cd "src/3. Retrieval Augmented Generation"
echo "OPENAI_API_KEY=your_key_here" > .env

Required API Keys

• OPENAI_API_KEY - Most modules
• ANTHROPIC_API_KEY - Claude examples
• TAVILY_API_KEY - Web search (optional)

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📝 License

Educational purposes only.