Video course · 7 chapters · 11 min · certificate
Retrieval Augmented Generation (RAG) and Vector Databases for Developers
Microsoft's Generative AI for Beginners lesson on RAG and vector databases: LLM limitations, how RAG grounds answers, its components, chunking and embeddings, similarity and relevance, building the application and evaluating with groundedness and relevance metrics.
What you'll learn
- Explain LLM limitations RAG addresses
- Describe RAG components and vector databases
- Chunk data and create embeddings
- Retrieve by similarity
- Evaluate RAG with groundedness and relevance
Chapters
7 chapters · 11:01-
1:51
01Intro Members
Introduction and limitations
Lesson 15.
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1:11
02RAG Members
Retrieval-augmented generation
Rooted in fact.
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1:08
03Components Members
Components and vector databases
Knowledge base.
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1:23
04Chunking Members
Data structure and embedding
Short passages.
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1:44
05Similarity Members
Similarity and relevance
Find matches.
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1:40
06Application Members
Building the application
End to end.
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2:04
07Evaluation Members
Evaluation
Three metrics.
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