Course
Vector Databases
Storing and searching embeddings with approximate nearest neighbors.
L3 · AdvancedFast-movingKnown~2 h
What you’ll learn
- Explain why vector search needs specialized indexes
- Describe how HNSW and other ANN indexes work and their tradeoffs
- Combine metadata filtering, hybrid search, and reranking, and choose an index
Prerequisites
embeddings
Module 1. Indexing
Why vector databases exist and how ANN indexes work.
Module 2. Retrieval Quality
Filtering, hybrid search, reranking, and index choice.