Retrieval-Augmented Generation (RAG) Fundamentals

This beginner-friendly course introduces Retrieval-Augmented Generation without requiring prior AI or machine learning experience. Learners will explore the complete RAG pipeline—from indexing and chunking private documents into vector databases to generating grounded, accurate answers that eliminate hallucinations. The curriculum covers core terminology, toolkits like LangChain and ChromaDB, real-world industry applications, and key differences between RAG and fine-tuning. Additionally, students will review design practices, common pitfalls, and advanced techniques such as hybrid search and re-ranking. To solidify their learning, the course features hands-on exercises, knowledge checks, and a capstone project to build a working knowledge assistant using free tools.