Gen-AI - Hands-on Workshop

Course Duration: 2 hours
Categories

GenAI Beyond Chat with RAG, Knowledge Graphs and Python

Course Description

In this GenAI and Neo4j workshop, you will learn how Neo4j can support your GenAI projects.

You will:

Use Vector indexes and embeddings in Neo4j to perform similarity and keyword search
Use Python and LangChain to integrate with Neo4j and OpenAI
Learn about Large Language Models (LLMs), hallucination and integrating knowledge graphs
Explore Retrieval Augmented Generation (RAG) and its role in grounding LLM-generated content

After completing this workshop, you will be able to explain the terms LLM, RAG, grounding, and knowledge graphs. You will also have the knowledge and skills to create simple LLM-based applications using Neo4j and Python.

Prerequisites

Before taking this course, you should have:

A basic understanding of Graph Databases and Neo4j
Knowledge of Python and capable of reading simple programs

While not essential, we recommend completing the GraphAcademy Neo4j Fundamentals course.

Duration

2 hours

What you need

To complete the practical tasks within this workshop, you will need:

Access to gitpod.io (you will need a Github account) or a local Python environment
An OpenAI billing account and API key

This workshop includes

7 lessons
11 short hands-on challenges

Get Support

If you find yourself stuck at any stage then our friendly community will be happy to help. You can reach out for help on the Neo4j Community Site, or head over to the Neo4j Discord server for real-time discussions.