Retrieval-Augmented Generation
Build retrieval-augmented generation from embeddings and semantic search to chunking and production retrieval
Understand the complete retrieval-augmented generation workflow. Learn how documents become embeddings, how semantic search finds relevant context, how chunking choices shape results, and how the pieces work together under production load.
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Instructor
Vivid Labs
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First lesson free · Join waitlist for full access
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Retrieval-Augmented Generation
Chapter List
Understand how retrieval-augmented generation grounds an LLM with relevant external context before it produces an answer.
Set the boundaries of a retrieval system: what belongs in the source collection, what the model may infer, and where grounding must win.
Move beyond exact keyword matching and retrieve passages whose meaning aligns with the user's question.
Tags
Trace how a retrieval pipeline reconstructs the right context from a larger source collection instead of sending everything to the model.