RAG Crash Course for Beginners

Learn how to build production-ready Retrieval Augmented Generation (RAG) systems from scratch in this comprehensive 59-minute tutorial that demystifies how AI systems like ChatGPT remember documents and search through company data. Start with the fundamentals by understanding what RAG is and when not to use it, then progress through hands-on labs covering keyword search techniques using TF-IDF and BM25 algorithms. Explore semantic search concepts and dive deep into embedding models, learning how they convert text into vectors and understanding the mathematical foundations including dot products. Master vector databases through practical ChromaDB implementation and discover various document chunking strategies that optimize information retrieval. Build a complete RAG pipeline architecture while learning about caching, monitoring, and error handling for production deployments. Practice everything covered through five interactive labs that provide real coding experience, from basic keyword search to implementing a full RAG system with vector databases and embedding models.