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AI Enhancement with Knowledge Graphs - Mastering RAG Systems · LearnSpace
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AI Enhancement with Knowledge Graphs - Mastering RAG Systems

Курс от Packt
Средний≈ 6.3 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Updated in May 2025. This course now features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Unleash the potential of AI systems by mastering Retrieval-Augmented Generation (RAG) techniques with Knowledge Graphs in this comprehensive course. You'll learn how to design, build, and query advanced Knowledge Graphs while integrating them with AI systems to boost contextual understanding and improve retrieval efficiency. The course begins with a solid introduction to Knowledge Graphs, including their structure, construction, and applications. You'll set up your development environment, dive into practical Neo4j implementations, and programmatically generate Knowledge Graphs. Through guided exercises, you'll extract real-world data, transform it into graph structures, and visually explore their interconnections. Moving further, you'll explore the synergy between Knowledge Graphs and RAG systems, creating vector indexes, embeddings, and integrating them into databases. Learn advanced querying methods, visualizations, and workflows for AI-powered use cases. By the end, you'll build a RAG-powered Knowledge Graph project, combining Neo4j and LangChain, to showcase the full flow of data transformation, retrieval, and application. This course is perfect for AI enthusiasts, data engineers, and developers eager to enhance their AI models with Knowledge Graphs. Prior experience with Python and basic AI concepts is recommended. Whether you’re at an intermediate or advanced level, you'll gain valuable, industry-relevant skills.

Навыки, которые вы освоите

Retrieval-Augmented GenerationGraph TheoryDevelopment EnvironmentQuery LanguagesInteractive Data VisualizationEmbeddingsGraphingAI WorkflowsData ProcessingVector DatabasesAI IntegrationsLLM ApplicationLarge Language Modeling

Программа курса

8 модулей · 47 учебных материалов

01Introduction4 материалов

Introduction

Introduction to the Course 'AI Enhancement with Knowledge Graphs – Mastering RAG Systems'ЧтениеIntroduction and Pre-requisitesВидеоCourse StructureВидеоFull Course ResourcesЧтение
02Development Environment Setup

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Packt - Course Instructors

Преподаватель курса

AI Enhancement with Knowledge Graphs - Mastering RAG Systems
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Обучение откроется на Coursera
в новой вкладке

Обучение на Coursera

≈ 6.3 ч

8 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Индонезийский, Испанский, Японский, Казахский, Венгерский

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3 материалов

Development Environment Setup

Development Environment Setup & the OpenAI Account - OverviewВидеоSetup the OpenAI API KeyВидеоDevelopment Environment Setup - AssessmentЗадание
03Knowledge Graph Deep Dive4 материалов

Knowledge Graph Deep Dive

Knowledge Graph Deep Dive - Definition and Key ConceptsВидеоKnowledge Graph Structure - Construction and ApplicationВидеоSummaryВидеоKnowledge Graph Deep Dive - AssessmentЗадание
04Hands-On: Knowledge Graph Deep Dive - Neo4j Introduction and Overview11 материалов

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

Building Knowledge Graphs & Neo4j Introduction and OverviewВидеоNeo4J - FundamentalsВидеоNeo4j Browser OverviewВидеоSetting up Neo4J - Create the Graph Database Instance and Connect to ItВидеоConnecting to Our Graph Database ProgrammaticallyВидеоPractice: Model a Knowledge GraphDIALOGUEProgrammatically creating Entities & Relationships Generating a Knowledge GraphВидеоRun a Simple Query - Get All Entities NamesВидеоRunning a Query to Get Paths-RelationshipsВидеоSummaryВидеоHands-On: Knowledge Graph Deep Dive - Neo4j Introduction and Overview - AssessmentЗадание
05Knowledge Graphs & RAG Systems6 материалов

Knowledge Graphs & RAG Systems

Knowledge Graph & RAG - Full OverviewВидеоHands-on - Extracting CSV file Data & Transform it Into a Knowledge GraphВидеоNeo4j Browser - View the Entire Graph VisuallyВидеоQuerying Knowledge Graph with LangChain WrappersВидеоSummaryВидеоKnowledge Graphs & RAG Systems - AssessmentЗадание
06Knowledge Graph & RAG - Index Creation and Vector Store - Embeddings4 материалов

Knowledge Graph & RAG - Index Creation and Vector Store - Embeddings

Creating a Vector Index, Creating Embeddings and Populating then Into the DBВидеоQuerying the Vector Index and Knowledge GraphВидеоSummaryВидеоKnowledge Graph & RAG - Index Creation and Vector Store - Embeddings - AssessmentЗадание
07Hands-on: User Cases - Graph Retrieval and RAG Systems - The Whole Flow11 материалов

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

Graph Retriever & Knowledge Graph - Full Flow OverviewВидеоHands-on: The Roman Empire RAG System and Knowledge GraphВидеоSetting up the Project and Loading Wikipedia Data and Splitting Docs into ChunksВидеоExtract Graph Data and Generate the Knowledge GraphВидеоPractice: Design a Hybrid Retrieval StrategyDIALOGUEVisualized the Whole Knowledge GraphВидеоGraph Retriever and Entity Parser SetupВидеоCreate the Full Text Index and Necessary Functions to Return EntitiesВидеоDefine the RAG Chain and Put it All Together - GraphRAGВидеоSummaryВидеоHands-on: User Cases - Graph Retrieval and RAG Systems - The Whole Flow - AssessmentЗадание
08Wrap up4 материалов

Wrap up

Next StepsВидеоConclusion to the Course 'AI Enhancement with Knowledge Graphs – Mastering RAG Systems'ЧтениеFull Course Practice AssessmentЗаданиеFull Course AssessmentЗадание