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所在平台: Udemy |
课程主页: https://www.udemy.com/course/java-spring-ai-neo4j-openai-knowledge-graph-rag/
课程评论：没有评论
**课程名称：** Java Spring AI, Neo4j, 和 OpenAI 助力知识图谱 RAG **课程概述：** 本课程旨在提升您在检索增强生成（Retrieval-Augmented Generation, RAG）方面的专业知识，重点介绍如何利用知识图谱来增强生成式AI的能力。RAG是一种强大的方法，能够帮助生成式AI访问预训练模型之外的信息，同时避免过度依赖模型本身提供事实性内容。RAG系统的有效性取决于快速识别并向大型语言模型（LLMs）提供最相关上下文的能力。 知识图谱能够通过提高性能、准确性、可追溯性和完整性来转型RAG系统。本课程将深入探讨将知识图谱应用于RAG（也称为GraphRAG）的有效性，帮助您解锁LLMs的潜力。 **您将学习到：** * **RAG系统入门：** 了解检索增强生成为何是增强AI的突破性工具。 * **知识图谱基础：** 掌握知识图谱的基本概念，包括其结构和数据关系，以及知识图谱如何增强RAG的数据建模。 * **从零开始实现GraphRAG：** 构建一个具备知识图谱的完整RAG系统，利用LLMs提取和组织信息。 * **从多数据源构建知识：** 学习如何将知识图谱与非结构化和结构化数据源集成。 * **知识图谱查询：** 获得使用领先工具和技术的实践经验。 **技术亮点：** * **Spring AI：** 来自Java Spring的新技术，帮助工程师轻松处理各种生成式AI和大型语言模型。 * **OpenAI：** 备受欢迎的创新生成式AI，是大型语言模型和AI领域的突破性工具。 * **Neo4j：** 图数据库和向量存储，可轻松与Spring AI集成，构建RAG和知识图谱。 * **Temporal：** 工作流编排平台，帮助工程师构建可靠的GraphRAG管道。 掌握这些高级AI技术将为您在当今快节奏、数据驱动的世界中提供显著优势，为您的职业生涯或在您所在领域的创新提供可行的见解。
Enhance Your Generative AI Expertise with Retrieval Augmented Generation (RAG) and Knowledge GraphRetrieval-augmented generation (RAG) is a powerful approach for utilizing generative AI to access information beyond the pre-trained data of Large Language Models (LLMs) while avoiding over-reliance on these models for factual content. The effectiveness of RAG hinges on the ability to quickly identify and provide the most relevant context to the LLM. Knowledge Graphs transforms RAG systems with improved performance, accuracy, traceability, and completeness.The RAG with Knowledge Graph, also known as GraphRAG, is an effective way to improve the capability of Generative AI. Take your AI skills to the next level with this ultimate course, designed to help you unlock the potential of LLMs by leveraging Knowledge Graphs and RAG systems.In this course, you will learn:Introduction to RAG Systems: Discover why Retrieval Augmented Generation is a groundbreaking tool for enhancing AI.Foundations of Knowledge Graphs: Grasp the basics of knowledge graphs, including their structure and data relationships. Understand how these graphs enhance data modeling for RAG.Implementing GraphRAG from Scratch: Build a fully operational RAG system with knowledge graphs. Use LLMs to extract and organize information.Building Knowledge From Multiple Data Sources: Learn to integrate knowledge graphs with unstructured and structured data sources.Querying Knowledge Graphs: Gain practical experience with leading tools and techniques.Technology Highlights:Spring AI: A new technology from famous Java Spring to help engineers work easily with various Generative AI and Large Language ModelsOpen AI: The innovative Generative AI that everyone loves. A groundbreaking tool for Large Language Models and AI.Neo4J: Graph database and Vector store that integrates easily with Spring AI to form RAG and Knowledge GraphTemporal: A workflow orchestrator platform to help engineers build a reliable GrahRAG pipeline.Mastering advanced AI techniques offers a significant edge in today's fast-paced, data-driven world. This course provides actionable insights to enhance your career or innovate in your field.
