GraphRAG: Knowledge Graphs for Better LLM Applications

Large Language Models (LLMs) are powerful, but they often struggle with factual accuracy, hallucination, or accessing up-to-date information. Knowledge graphs, combined with Retrieval Augmented Generation (RAG), offer a robust solution to ground LLMs in verified data. This course will guide you through the principles of GraphRAG, enabling you to design and implement LLM applications that leverage structured knowledge for enhanced precision and relevance. You will gain the skills to build intelligent systems capable of answering complex queries with grounded, verifiable information. What you'll learn: * Understand the core concepts of Large Language Models (LLMs) and their inherent limitations in factual recall. * Learn the fundamentals of Knowledge Graphs, including their structure, creation, and benefits for information retrieval. * Explore Retrieval Augmented Generation (RAG) principles and how they enhance LLM performance and reduce hallucination. * Apply GraphRAG techniques to integrate knowledge graphs into LLM workflows for improved accuracy and contextual understanding. * Practice designing effective prompts for RAG-enabled LLM applications to optimize information retrieval and generation. * Understand basic methods for evaluating the performance and factual grounding of RAG systems. * Build a foundational understanding of how to architect and implement robust LLM applications using knowledge graphs. The course begins with foundational concepts of LLMs and knowledge graphs, then progresses to the theory and practical application of RAG and GraphRAG. You will learn to combine these technologies to create intelligent systems, culminating in an understanding of how to design and evaluate effective LLM solutions. This course is for beginners interested in developing intelligent applications with Large Language Models and structured data. No prior experience with knowledge graphs or advanced LLM development is required. Begin your journey to building smarter, more reliable LLM applications today.