Oreilly – A Simple Guide to Retrieval Augmented Generation, Video Edition 2025-6

A Simple Guide to Retrieval Augmented Generation, Video Edition. This course provides a comprehensive and easy-to-understand overview of the Retrieval Augmented Generation (RAG) concept, designed for beginners. RAG combines data from a large language model (LLM) with information retrieved from an external knowledge base to answer specific questions, provide up-to-date information, and engage in dynamic conversations. The course goes from the basics of RAG to more advanced methods such as working with multimodal data (images, spreadsheets, etc.) by explaining the indexing and production pipelines. In this guide, you will learn how RAG produces more accurate answers and avoid common model errors by retrieving relevant information from sources such as vector databases or organizational documents. You will also implement a complete RAG system using practical examples in Python and tools such as LangChain. This course is designed so that even those new to the field of artificial intelligence can easily understand and implement the concepts and applications of RAG.

What you will learn

• Components of a RAG System: You will learn about the main components of a RAG system and how they are used.
• How to Create a RAG Knowledge Base: You will learn how to create a knowledge base for your RAG system.
• Indexing and Generation Pipeline: You will learn how the Indexing and Generation pipeline works.
• Evaluating a RAG System: You will learn how to evaluate the performance and accuracy of a RAG system.
• Advanced RAG Strategies: You will learn more advanced strategies for improving RAG.
• RAG Tools, Technologies, and Frameworks: You know the important tools and frameworks for implementing RAG, such as LangChain.
• Build a complete system: With step-by-step instructions, you build a complete RAG system yourself.

This course is suitable for people who:

• Data scientists, engineers, and technology managers: For these individuals, no prior experience in the LLM field is required.
• Beginners in the field of AI: People who have just entered the world of AI and want to get acquainted with RAG concepts.

Course details

• Publisher: Oreilly
• Instructor: Abhinav Kimothi
• Training level: Beginner to advanced
• Training duration: 7 hours and 5 minutes

Course topics