This micro-learning course gives you a clear, practical introduction to Retrieval-Augmented Generation (RAG), designed specifically for small businesses and new AI builders. You’ll learn what RAG is, why it matters, and how it turns your own documents into powerful, domain-specific knowledge for chatbots and automation. We’ll walk through two complete RAG pipelines step-by-step: one built from scratch in Python, and one using LangChain to simplify the workflow. You’ll explore chunking, embeddings, vector search, retrieval, prompting, and evaluation all inside Google Colab with real examples. By the end, you’ll know exactly how to build a working RAG system and how to apply it to your own business data. No extensive machine learning experience required... just curiosity, a Google account, an OpenAI API, and a basic understanding of Python as a coding language.