Learn how Neo4j powers Generative AI applications

Discover how Neo4j combines knowledge graphs, vector search, and large language models to power intelligent Generative AI applications. In this hands-on virtual workshop, you'll learn how to use Neo4j to build Retrieval-Augmented Generation (RAG) and GraphRAG applications that deliver more accurate, context-aware, and explainable AI experiences.

Designed for developers, AI engineers, data scientists, architects, and technical practitioners with a basic understanding of Neo4j, this workshop combines practical exercises with real-world AI development techniques. You'll build a knowledge graph from structured and unstructured data, use vector indexes and embeddings for similarity search, create different retrieval strategies, and build a conversational AI agent using Neo4j, Python, and LangChain.

You will learn:

• The fundamentals of Generative AI, Retrieval-Augmented Generation (RAG), and GraphRAG
• How to build a knowledge graph from structured and unstructured data
• How to use vector indexes and embeddings in Neo4j for similarity search
• How to create vector, vector + Cypher, and Text-to-Cypher retrievers
• How to build a conversational AI agent using Neo4j, Python, and LangChain

Prerequisites

To get the most out of this workshop, you should have:

• A basic understanding of graph databases and Neo4j
• The ability to read and understand basic Cypher queries
• Basic knowledge of Python and the ability to read and execute simple programs

We also recommend completing the Neo4j Fundamentals course on GraphAcademy before attending.

Requirements

Please join the session from a desktop or laptop computer so you can participate in the hands-on exercises. If you're using a work-issued laptop with firewall or security restrictions that you can't control, we recommend using a personal laptop instead.

Space is limited, so register today to secure your place!