{"id":11587,"date":"2026-08-10T10:34:14","date_gmt":"2026-08-10T10:34:14","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/oreilly-a-simple-guide-to-retrieval-augmented-generation-video-edition-2025-6\/"},"modified":"2026-08-10T10:34:14","modified_gmt":"2026-08-10T10:34:14","slug":"oreilly-a-simple-guide-to-retrieval-augmented-generation-video-edition-2025-6","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/oreilly-a-simple-guide-to-retrieval-augmented-generation-video-edition-2025-6\/","title":{"rendered":"Oreilly \u2013 A Simple Guide to Retrieval Augmented Generation, Video Edition 2025-6"},"content":{"rendered":"
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Description<\/span><\/h2>\n

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.<\/span><\/p>\n

What you will learn<\/span><\/h3>\n