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所在平台: Udemy |
课程主页: https://www.udemy.com/course/rag-powered-ai-build-a-chatbot-inpython-langchain-ollama/
课程评论：没有评论
Coursera 课程：使用 RAG、LangChain 和 Ollama 用 Python 构建 AI 聊天机器人 本课程面向 Python 开发者、数据科学家和 AI 爱好者，深入讲解检索增强生成 (RAG) 技术，并教授如何使用 Ollama、LangChain 和向量嵌入构建智能文档问答应用。 **您将学到：** * RAG 的概念及其增强 LLM 的能力 * 如何使用 LangChain 处理 PDF 文档 * 从 PDF 中提取文本并将其分块以提高检索效率 * 如何生成向量嵌入以实现更准确的语义搜索 * 如何使用向量数据库查询和检索相关文档信息 * 如何集成本地 LLM (Ollama) 生成上下文感知的响应 * 优化 AI 模型响应的实用技巧 **课程亮点：** * 提供搭建开发环境（VS Code、Python 及必需库）的分步指南 * 通过实战项目，从零开始构建功能完善的 PDF 问答聊天机器人 * 掌握 Ollama（运行本地 LLM 的工具）和 LangChain（文档 AI 处理框架） * 理解向量嵌入的基础知识及其对 AI 系统搜索和响应精度的提升 * 提升 Python 技能，将机器学习技术应用于实际场景 **课程目标：** 学完本课程后，您将能够构建和部署自己的 AI 驱动的文档问答聊天机器人，为专业应用、个人项目或深入研究 AI 概念打下基础。 **适合人群：** * 希望将 AI 集成到项目中的 Python 开发者 * 寻求将 RAG 技术应用于工作流程的数据科学家 * 希望深入了解 LLM 及 Ollama、LangChain 等 AI 工具的 AI 爱好者 * 对 AI 和机器学习应用开发感兴趣的初学者
Course Description:Welcome to "Building a RAG Application with Ollama, LangChain, and Vector Embeddings in Python"! This hands-on course is designed for Python developers, data scientists, and AI enthusiasts looking to dive into the world of Retrieval-Augmented Generation (RAG) and learn how to build intelligent document-based applications.In this course, you will learn how to create a powerful PDF Q & A chatbot using state-of-the-art AI tools like Ollama, LangChain, and Vector Embeddings. You'll gain practical experience in processing PDF documents, extracting and generating meaningful information, and integrating a local Large Language Model (LLM) to provide context-aware responses to user queries.What you will learn:What is RAG (Retrieval-Augmented Generation) and how it enhances the power of LLMsHow to process PDF documents using LangChainExtracting text from PDFs and splitting it into chunks for efficient retrievalGenerating vector embeddings using semantic search for better accuracyHow to query and retrieve relevant information from documents using Vector DBIntegrating a local LLM with Ollama to generate context-aware responsesPractical tips for fine-tuning and improving AI model responsesCourse Highlights:Step-by-step guidance on setting up your development environment with VS Code, Python, and necessary libraries.Practical projects where you'll build a fully functional PDF Q & A chatbot from scratch.Hands-on experience with Ollama (a powerful tool for running local LLMs) and LangChain (for document-based AI processing).Learn the fundamentals of vector embeddings and how they improve the search and response accuracy of your AI system.Build your skills in Python and explore how to apply machine learning techniques to real-world scenarios.By the end of the course, you'll have the skills to build and deploy your own AI-powered document Q & A chatbot. Whether you are looking to implement AI in a professional setting, develop your own projects, or explore advanced AI concepts, this course will provide the tools and knowledge to help you succeed.Who is this course for?Python Developers who want to integrate AI into their projects.Data Scientists looking to apply RAG-based techniques to their workflows.AI Enthusiasts and learners who want to deepen their knowledge of LLMs and AI tools like Ollama and LangChain.Beginners interested in working with AI and machine learning to build real-world applications.Get ready to dive into the exciting world of AI, enhance your Python skills, and start building your very own intelligent PDF-based chatbot!
