Build a RAG system

Chunk and embed your documents, retrieve the passages that answer a question, and generate from them.

Embeddings and a vector store first, then the pipeline that uses them.

2 courses · 14 lessons · 55 min

  1. Embeddings and similarity search

    Intermediate

    Turning text into vectors, and the store that finds the nearest ones.

    6 lessons · 20 min · Retrieval and knowledge

  2. Build a RAG pipeline

    Intermediate

    Chunking, storage, retrieval and generation, and the failure each stage introduces.

    8 lessons · 35 min · Retrieval and knowledge