Course
Neo4j and Generative AI Workshop
Learn how to build GraphRAG workflows with Neo4j, Python, and LLM-powered retrieval techniques.
About this course
In this 2-hour course, you will learn
Welcome to GraphAcademy and the Neo4j and Generative AI workshop.
In this workshop you will:
- Learn about Generative AI, RAG, and GraphRAG.
- Build a knowledge graph from unstructured and structured data.
- Use Vector indexes and embeddings in Neo4j to perform similarity search.
- Create vector, vector + cypher, and text to Cypher retrievers.
- Build a conversational agent using Neo4j, Python, and LangChain
Prerequisites
Before taking this workshop, you should have:
- A basic understanding of Graph Databases and Neo4j
- Able to read and understand basic Cypher queries
- Knowledge of Python and capable of reading and executing simple programs
To take this course we recommend that you have taken these beginner courses in GraphAcademy:
The fundamentals of Generative AI and Large Language Models (LLMs)
What Retrieval-Augmented Generation (RAG) is and why it is important
How GraphRAG can improve the quality of LLM-generated content
How to build knowledge graphs from unstructured PDF documents using entity extraction and relationship mapping
How to enrich knowledge graphs with structured data
How to use Vectors in Neo4j for similarity search
To build different types of retrievers using the neo4j-graphrag for Python package.
To build a conversational agent using Neo4j, Python, and LangChain.
Course content