Master's year 2 · 4 days - 28 hours

Generative AI: from LLMs to agents

Understand and use generative models: LLMs, prompt engineering, RAG, agents and deployment, with hands-on Python labs.

Learning objectives

• Explain how a transformer and an LLM work
• Design robust prompts and evaluate them
• Build a RAG pipeline on business documents
• Orchestrate a simple agent with LangChain or LangGraph
• Assess the limits, risks and costs of a generative AI project

Course outline Free preview

1. Overview of generative AI
2. Transformers, tokens and embeddings
3. Prompt engineering and evaluation
4. RAG: chunking, vector indexing, retrieval
5. Agents and tools
6. Production and ethics