Engineering Intermediate Premium
RAG Systems: Retrieval-Augmented Generation
Build AI systems that answer questions using your own data by combining search with language model generation.
Retrieval-Augmented Generation is one of the most practical patterns in production AI. This course covers document ingestion, chunking strategies, embedding models, vector search, reranking, and prompt construction — everything needed to build a RAG pipeline that returns accurate, grounded answers.
Lessons (7)
Document Ingestion and Chunking
25 min
Embedding Models and Vector Storage
25 min
Search and Reranking Strategies
25 min
Prompt Construction for RAG
20 min
Evaluating RAG Quality
30 min
Production RAG Architecture
35 min
