Master Knowledge Graph Retrieval-Augmented Generation with Neo4j

In this GraphRAG course, you will learn how to use a knowledge graph to implement an RAG application with Neo4j and OpenAI ChatGPT, enhancing response accuracy and reducing hallucinations.

Intermediate

9 Lessons

Certificate of Completion

In this GraphRAG course, you will learn how to use a knowledge graph to implement an RAG application with Neo4j and OpenAI ChatGPT, enhancing response accuracy and reducing hallucinations.

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Explanations

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This course includes

17 Playgrounds

6 Quizzes

This course includes

17 Playgrounds

6 Quizzes

Course Overview

Knowledge graphs are powerful tools that structure information into entities and relationships, making data more accessible and meaningful for AI applications. They are essential for enhancing the performance of LLMs by providing structured context, improving response accuracy and cohesiveness, and reducing hallucinations on datasets outside the LLM’s training data. In this course, you’ll explore knowledge graphs for retrieval-augmented generation (RAG) and dive deep into traditional to advanced NER and re...Show More

What You'll Learn

An understanding of fundamental concepts of generative AI, large language models (LLMS), and retrieval-augmented generation (RAG)

Familiarity with differences between RAG with knowledge graphs and RAG with vector databases

Hands-on experience implementing knowledge graph RAG with Neo4j and OpenAI GPT-4

The ability to build knowledge graphs for text documents from scratch using OpenAI GPT-4 for named entity recognition and relationship extraction

The ability to store entities and relationships in the Neo4j graph database using Cypher query language

Hands-on experience using Cypher to retrieve relevant information from the knowledge graph to include it in the prompt to LLM

The ability to build a personalized question-answering chatbot with graph RAG

What You'll Learn

An understanding of fundamental concepts of generative AI, large language models (LLMS), and retrieval-augmented generation (RAG)

Course Content

Introduction to the Course

Get familiar with integrating generative AI with Neo4j for efficient knowledge graph management.

Getting Started

Understanding the Path to Graph RAG

Constructing Knowledge Graphs

Get started with traditional and improved entity extraction, and large-scale text chunking.

Traditional NER and Relationship Extraction Techniques Improved Entity and Relationship Extraction Using LLMs Chunking: Entity and Relationship Extraction with LLMs at Scale

Create a Knowledge Graph from Text

Project

Neo4j: Storing Entities and Relationships to Graph Database

Go hands-on with Neo4j to store and manage entities and relationships efficiently.

Introduction to Neo4j Storing LLM Extracted Entities and Relationships in Neo4j

Integrating Knowledge Graphs with LLMs

Enhance your skills in integrating Knowledge Graph-based RAG with Neo4j to improve chatbot AI.

Knowledge Graph-based RAG Conclusion

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