Vector Databases & RAG in Practice | WebMagic Informatica
Agentic AI
Vector Databases & RAG in Practice
Learn embeddings and vector databases (Pinecone, Chroma, pgvector), then use them to build Retrieval-Augmented Generation pipelines — chunking, retrieval strategies, hybrid search, and evaluation.
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Live Instructor SessionsHands-on Labs & ProjectsCertificate of CompletionCareer Support & Guidance
Duration41 min
Curriculum3 sections · 7 lessons
Tools you'll learn
PPinecone
CChroma
Ppgvector
Prerequisites
Working with LLM APIs
Learning outcomes
What you'll be able to do by the end
Generate and store embeddings in a vector database
Design chunking and retrieval strategies for RAG
Evaluate RAG pipeline quality
Project: build a working RAG pipeline over a real document set