Constructing Knowledge Graphs with Neo4j GraphRAG for Python

In this hands-on course, you will learn how to create knowledge graphs using Neo4j GraphRAG for Python.

You will:

• Use the neo4j_graphrag Python package to build knowledge graphs from unstructured data.
• Add structured data to the knowledge graph to improve LLM responses.
• Create retrievers to search the knowledge graph.
• Learn how you can customize the build process to suit your data and use case.

Finally, you will use what you have learned to build a knowledge graph from your data.

Prerequisites

This is an advanced course and you should:

• Understand graph and Neo4 fundamental concepts - Neo4j and Graph Fundamentals.
• Have an understanding of how Generative AI, LLMs, and vector indexes are related to Neo4j - Neo4j & GenerativeAI Fundamentals.
• Be able to read and write simple Cypher queries - Cypher Fundamentals.
• Understand how you can use an LLM to generate a knowledge graph - LLM Knowledge Graph Construction.
• Have experience with programming in Python.