Gen-AI - Hands-on Workshop
Course Description
In this GenAI and Neo4j workshop, you will learn how Neo4j can support your GenAI projects.
You will:
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Use Vector indexes and embeddings in Neo4j to perform similarity and keyword search
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Use Python and LangChain to integrate with Neo4j and OpenAI
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Learn about Large Language Models (LLMs), hallucination and integrating knowledge graphs
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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:
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A basic understanding of Graph Databases and Neo4j
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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:
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Access to gitpod.io (you will need a github, gitpod, or bitbucket account) or a local Python environment
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An OpenAI billing account and API key
This workshop includes
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7 lessons
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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.
Feedback
If you have any comments or feedback on this course you can email us on graphacademy@neo4j.com.