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Master Knowledge Graph Retrieval-Augmented Generation with Neo4j

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

Intermediate

9 Lessons

Certificate of Completion

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

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Explanations

AI-POWERED

Explanations

This course includes

17 Playgrounds

6 Quizzes

Course Overview

What You'll Learn

Course Content

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, 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 relat...Show More

Knowledge graphs are powerful tools that structure information into entities and relationships, making data more accessible and ...Show More

What You'll Learn

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

Differences between RAG with knowledge graphs and RAG with vector databases

Implementing knowledge graph RAG with Neo4j and OpenAI GPT-4

Building knowledge graph for text documents from Scratch using OpenAI GPT-4 for named entity recognition and relationship extraction

Storing entities and relationships in the the Neo4j graph database using Cypher query language

Using Cypher to retrieve relevant information from the knowledge graph to include it in the prompt to LLM

Building a personalized question-answering chatbot with graph RAG

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

Course Content

Introduction to the Course

2 Lessons

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

Getting Started

Understanding the Path to Graph RAG

Constructing Knowledge Graphs

3 Lessons

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

Neo4j: Storing Entities and Relationships to Graph Database

2 Lessons

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

2 Lessons

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

Knowledge Graph-based RAG

Conclusion

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