A vector database stores data as lists of numbers called embeddings, which lets it search by meaning instead of matching exact keywords. It's the piece behind a lot of recommendation systems, RAG apps, and AI agents.

We just published a comprehensive course on the freeCodeCamp.org YouTube channel that will teach you how vector databases work, starting with the math and ending with a working semantic search project. This course is from codeEdx, whose instructor has worked as a software engineer for 15 years and as a lead AI engineer for the last four. No prior knowledge is required.

In this course, you will learn:

Vectors & Similarity Math

Learn what a vector is and how cosine similarity and Euclidean distance measure how close two pieces of data are.

Tokens & Tokenization

See why AI models can't read raw text and how a tokenizer splits a word like "indivisible" into more than one token.

Embeddings & Embedding Models

Understand how text becomes vectors that capture meaning, including the classic king…