Supercharge Ai With Knowledge Graphs: Rag System Mastery

Enhance Large Language Models Using Structured Context and Retrieval-Augmented Generation - Neo4j, LangChain, Cypher

What you'll learn

Understand Knowledge Graph Fundamentals

Implement Knowledge Graphs with Neo4j

Enhance the accuracy of RAG application with Knowledge Graphs

Create and Utilize Full-Text Search Indexes

Requirements

Basic Understanding of Databases

Fundamental Programming Skills

Basic Understanding of AI, LLM

Description

Are you ready to take your AI skills to the next level? Welcome to "Supercharge AI with Knowledge Graphs: RAG System Mastery", the ultimate course designed to unlock the full potential of Large Language Models (LLMs) using cutting-edge techniques in Knowledge Graphs and Retrieval-Augmented Generation (RAG) systems.What You Will Learn:Foundations of Knowledge Graphs: Understand the core concepts, structure, and components of knowledge graphs and how they represent complex data relationships.Introduction to RAG Systems: Learn what Retrieval-Augmented Generation is and why it’s a game-changer for improving the performance of AI models.Integrating Knowledge Graphs with LLMs: Discover how to combine knowledge graphs with large language models to provide structured, relevant context and boost AI capabilities.Building and Querying Knowledge Graphs: Gain hands-on experience in creating and querying knowledge graphs using popular tools and technologies.Optimizing AI with Structured Data: Explore strategies for enhancing AI performance by leveraging the structured data provided by knowledge graphs.Real-World Applications: Dive into practical examples and case studies showcasing the use of knowledge graphs in various industries such as healthcare, finance, and more.Advanced Techniques: Learn advanced methods for fine-tuning LLMs and integrating them with RAG systems for superior results.Course Highlights:Hands-On Projects: Work on real-world projects to build and optimize knowledge graphs and integrate them with AI models.Expert Instructors: Learn from industry experts with years of experience in AI, knowledge graphs, and RAG systems.Interactive Content: Engage with interactive lectures, quizzes, and assignments to reinforce your learning.Community Support: Join a community of learners and professionals to share insights, ask questions, and collaborate on projects.Who This Course Is For:AI and Machine Learning Enthusiasts: Individuals looking to deepen their understanding of AI and enhance the performance of their models.Data Scientists and Engineers: Professionals seeking to leverage knowledge graphs and RAG systems for more effective data management and analysis.Developers and Programmers: Technologists interested in integrating cutting-edge AI techniques into their applications.Business Analysts and Managers: Decision-makers aiming to harness the power of AI for strategic insights and competitive advantage.Why Enroll?In today’s data-driven world, the ability to utilize structured data and advanced AI techniques is a significant advantage. This course equips you with the knowledge and skills to stay ahead of the curve, providing practical, actionable insights that you can apply immediately. Whether you're looking to enhance your career, innovate in your current role, or simply explore the fascinating world of AI, this course offers the comprehensive learning experience you need.Enroll now in "Supercharge AI with Knowledge Graphs: RAG System Mastery" and transform your understanding of AI, knowledge graphs, and Retrieval-Augmented Generation. Take the first step towards mastering the future of AI today!

Overview

Section 1: Introduction

Lecture 1 Introduction and Pre-requisites

Lecture 2 Course Structure

Section 2: Download Code

Lecture 3 Get code

Section 3: Development Environment Setup

Lecture 4 Development Environment Setup & the OpenAI Account- Overview

Lecture 5 Setup the OpenAI API Key

Section 4: Knowledge Graph Deep Dive

Lecture 6 Knowledge Graph Deep Dive - Definition and Key Concepts

Lecture 7 Knowledge Graph Structure - Construction and Application

Lecture 8 Summary

Section 5: Hands-On: Knowledge Graph Deep Dive -Neo4j Introduction and Overview

Lecture 9 Building Knowledge Graphs & Neo4j Introduction and Overview

Lecture 10 Neo4J - Fundamentals

Lecture 11 Neo4j Browser Overview

Lecture 12 Setting up Neo4J - Create the Graph Database Instance and Connect to It

Lecture 13 Connecting to Our Graph Database Programmatically

Lecture 14 Programmatically creating Entities & Relationships Generating a Knowledge Graph

Lecture 15 Run a Simple Query - Get All Entities Names

Lecture 16 Running a Query to Get Paths-Relationships

Lecture 17 Summary

Section 6: Knowledge Graphs & RAG Systems

Lecture 18 Knowledge Graph & RAG - Full Overview

Lecture 19 Hands-on - Extracting CSV file Data & Transform it Into a Knowledge Graph

Lecture 20 Neo4j Browser - View the Entire Graph Visually

Lecture 21 Querying Knowledge Graph with LangChain Wrappers

Lecture 22 Summary

Section 7: Knowledge Graph & RAG - Index Creation and Vector Store - Embeddings

Lecture 23 Creating a Vector Index, Creating Embeddings and Populating then Into the DB

Lecture 24 Querying the Vector Index and Knowledge Graph

Lecture 25 Summary

Section 8: Hands-on: User Cases - Graph Retrieval and RAG Systems - The Whole Flow

Lecture 26 Graph Retriever & Knowledge Graph - Full Flow Overview

Lecture 27 Hands-on: The Roman Empire RAG System and Knowledge Graph

Lecture 28 Setting up the Project and Loading Wikipedia Data and Splitting Docs into Chunks

Lecture 29 Extract Graph Data and Generate the Knowledge Graph

Lecture 30 Visualized the Whole Knowledge Graph

Lecture 31 Graph Retriever and Entity Parser Setup

Lecture 32 Create the Full Text Index and Necessary Functions to Return Entities

Lecture 33 Define the RAG Chain and Put it All Together - GraphRAG

Lecture 34 Summary

Section 9: Wrap up

Lecture 35 Next Steps

Data Scientists and Analysts,Software Developers and Engineers,AI and Machine Learning Enthusiasts,Business Intelligence Professionals