Neo4j & GenerativeAI Fundamentals

Course Duration: 2 hours
Categories

Learn how Neo4j and GraphRAG can support your Generative AI projects

Course Description

In this course, you will learn how Neo4j and Knowledge Graphs can help you make work with Generative AI (GenAI) applications.

You will learn why graph databases are a reliable option for grounding GenAI models, using Neo4j to provide factual, reliable information to stop the LLM from giving false information, also known as hallucination.

You will learn about:

Embeddings and vector indexes, how they are used in GenAI, and how to use them in Neo4j.
RAG (Retrieval Augmented Generation) and how GraphRAG builds on it to provide a graph-based approach to providing context to Generative AI models.
How to use the Neo4j GraphRAG for Python package to interact with AI models and Neo4j.

This course uses models from OpenAI, although you can use the model and supplier of your choice.

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

We recommend taking the Neo4j Fundamentals course.

To complete the practical tasks within this course, you will need an OpenAI API key.

Duration

2 hours

What you will learn

The fundamentals of Generative AI, Large Language Models (LLMs), and their limitations.
How providing context improves the accuracy of Generative AI responses.
About Retrieval Augmented Generation (RAG) and how it combines retrieval and generation for better answers.
How vectors and embeddings enable semantic search and contextual retrieval in Neo4j.
Practical skills in building and querying knowledge graphs from both unstructured and structured data.
How to use the Neo4j GraphRAG for Python package to integrate vector search, graph traversal, and natural language querying for enhanced AI applications.

This course includes

15 lessons
2 short optional challenges
12 simple quizzes to support your learning

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.