All GuidesGuide 05
Intermediate • ~50min

RAG — Retrieval-Augmented Generation

Ground AI in your documents with RAG. Learn chunking strategies, vector embeddings, and hallucination reduction techniques.

Reduce hallucinations by ensuring each response can be linked to a controlled documentary source.

Objectives

01Explain the principles of Retrieval-Augmented Generation
02Structure a documentary context adapted to prompts
03Implement a local mini-RAG with citations

Contents

Section 01
Principle of contextual anchoring.
Section 02
Split and vectorize a reference corpus.
Section 03
Optimize query formulation to avoid context loss.
Section 04
Create a local business assistant citing its sources.

Skills

Build an indexed knowledge base for an AI assistant.Evaluate the relevance of a cited response.Anchor generation on verifiable sources.

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Frequently Asked Questions

What is the "RAG — Retrieval-Augmented Generation" module?+

"RAG — Retrieval-Augmented Generation" is a Intermediate • ~50min-level online training module. Ground AI in your documents with RAG. Learn chunking strategies, vector embeddings, and hallucination reduction techniques.

Are there any prerequisites for this module?+

Yes, we recommend completing Module 4 before starting this module.

Is this module free?+

Yes, this module is completely free and accessible without a paid subscription.

What will I learn in this module?+

Build an indexed knowledge base for an AI assistant.. Evaluate the relevance of a cited response.. Anchor generation on verifiable sources..