Vector similarity search is a key building block for modern AI applications. This learning session breaks down the fundamentals: what embeddings represent, how similarity is computed, and how indexing affects performance; followed by a hands-on demonstration in Python using python-oracledb and Oracle Database 26ai. You will gain a practical checklist for designing and implementing similarity search in your own systems.