Retrieval Augmented Generation Explained for Beginners - RAG in LLMs

Explore Retrieval Augmented Generation (RAG) for beginners in this comprehensive video tutorial. Delve into the fundamentals of Large Language Models (LLMs) and RAG, covering key components like retrieval and generation. Learn about the RAG workflow, practical applications, and challenges such as hallucinations. Gain hands-on experience with RAG implementation using LangChain, from importing libraries to detailed demonstrations. Master essential concepts and terminology, understand the limitations of LLMs, and discover how RAG addresses these challenges. Follow along with step-by-step instructions for implementing RAG, and conclude with a summary of key takeaways. Perfect for those looking to enhance their understanding of advanced AI techniques in natural language processing.

Introduction
Introduction to LLMs
Limitations of LLMs
Introduction to RAG
RAG Basics Concepts and Terminology
Key Components - Retrieval and Generation
Workflow of RAG
Applications of RAG
Hallucinations in RAG
Steps to implement RAG with LangChain
Hands-on RAG - Importing Libraries
Hands-on RAG in detail
RAG - Summary