Vector Databases: A Deep Dive
Course Overview
Intermediate
Free Course
For engineers building search or RAG who need to choose, size and run a vector database. You will learn how ANN indexes and similarity metrics work, compare Pinecone, Qdrant, Weaviate and pgvector, and benchmark recall, latency and cost on your own data.
Instructor: Jaidev
Sections: 3
Course Content
Section 1: Vector DB Fundamentals
How vector search turns meaning into geometry, which index families make it fast, and which similarity metric to use for which data.
Section 2: Practical Implementations
What Pinecone, Qdrant and Weaviate each do well, the code you write against each, and a way to choose between them from your own scale, traffic and budget.
Section 3: Mini Project
Run a benchmark of FAISS against Qdrant that a sceptical reviewer would accept: exact ground truth, recall-versus-latency curves, measured memory and a cost model.