GraphRAG Essential Training
GraphRAG Essential Training
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 33m | 235 MB
Instructor: Dr. Clair Sullivan
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 1h 33m | 235 MB
Instructor: Dr. Clair Sullivan
This beginner-friendly course introduces the fundamentals of GraphRAG (Graph Retrieval-Augmented Generation), a cutting-edge technique that combines knowledge graphs with generative AI to enhance contextual relevance and precision. Designed for professionals and students new to GraphRAG, the course covers key concepts, including graph structures, nodes, edges, and relationships, as well as practical skills in building and configuring GraphRAG models. Explore how to integrate GraphRAG into existing workflows to create enriched, data-driven AI applications, through hands-on exercises and real-world examples. By the end of the course, you will be able to identify use cases and implement GraphRAG effectively in a generative AI pipeline.
Learning objectives
- Understand and apply essential graph principles and structures, such as nodes, edges, and relationships, to enhance retrieval in AI applications.
- Identify practical use cases for GraphRAG such as the minimization of hallucinations and determine how to leverage it effectively in projects.
- Write basic GraphRAG software to combine graph-based knowledge with generative AI utilizing basic Python and Neo4j.
- Integrate GraphRAG with other NLP tools to create dynamic and contextually enriched AI responses utilizing standard large language models (LLMs) such as ChatGPT, Mistral, etc.
GraphRAG Essential Training
