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所在平台: Udemy |
课程主页: https://www.udemy.com/course/langchain-mastery-most-practical-course-to-build-ai-apps/
课程评论：没有评论
课程名称：LangChain Mastery - 最实用的AI应用构建课程 课程概述： 本课程基于最新的LangChain版本0.3，覆盖LangSmith，旨在为您提供全面的实践经验，从基础概念到高级AI应用，帮助您构建由AI驱动的工具、自动化数据工作流程以及利用最新的LLM技术。课程将提供互动的实际体验，采用简单的三步法：为什么、什么以及如何，指导您应用LangChain解决实际问题。 适合人群： - IT行业的新手：如果您对生成AI和大型语言模型（LLM）不太熟悉，但对IT行业有所了解，本课程将从基础开始，帮助您在课程结束时构建高级应用。 - 职业转型者：如果您想从其他领域转型进入IT行业，并希望深入生成AI领域，本课程将为您提供扎实的基础和实用技能，助您启动职业生涯。 - 有一定生成AI经验的学习者：对于那些对生成AI稍有了解，想深入学习LangChain的人，本课程将提升您的理解和技能。 - 经验丰富的AI开发者：如果您曾经构建过生成AI应用，但是信息来源零散，本课程将提供结构化和全面的指南，帮助您正确构建AI应用。 您将学到的内容： 通过实践项目，掌握LangChain及其生态系统的重要技能，包括： - 理解LLM和AI基础：涵盖LLM的运作方式、提示词、标记等基础知识，奠定坚实的基础。 - LangChain入门：设置环境、编写您的第一个生成AI代码，并探索LangChain的优势。 - 模型学习：了解聊天模型和LLM，参与动手项目。 - 提示词和输出解析：掌握提示词创建和输出解析，包括处理JSON的实际应用。 - Streamlit用于AI应用：构建用户友好的AI应用界面。 - 链接探索：学习LangChain链和可运行项，构建视频分析器、简历增强器和邮件生成器等应用。 - 内存管理：提升应用中的对话流，与LangChain的内存管理相结合。 - 提示工程：深入学习高级提示工程技术。 - 实际LLM用例：探索LLM的实际应用，了解生成AI的最大价值所在。 - RAG：与您的数据合作，创建QA机器人、摘要工具和比较工具。 - LangSmith：使用LangSmith进行调试和评估LangChain应用。 - 高级RAG：扩展RAG概念，进行多查询和索引构建更复杂的应用。 - 回调实现：优化和监控应用工作流。 - 部署和共享AI应用：在Streamlit Cloud和Hugging Face Spaces上部署您的AI应用，轻松共享项目。 课程结构与收益： 本课程的主要优势在于其简易性——将复杂概念拆解为易于理解的解释，使理论和实际应用对所有学习者都可接触。项目驱动学习：每个部分都包含互动项目，允许学员将概念直接应用于实际场景。结构化学习路径：主题组织合理，从基础到高级，全面理解。 通过本课程，您将能够： - 构建、调试和部署针对实际问题的LangChain应用。 - 实施有效的提示工程技术，并处理复杂的代理工作流。 - 使用Streamlit创建动态且用户友好的界面，并利用内存管理AI应用中的上下文。 - 使用LangSmith优化您的应用，并自信部署解决方案。 加入我们，从今天起开始构建强大的AI应用吧！
Course is created with latest LangChain Version 0.3 and also covered LangSmith.Welcome to LangChain Mastery - Most Practical Course To Build AI Apps! This course is designed to give you a comprehensive, hands-on experience with LangChain, covering everything from foundational concepts to advanced AI applications. Whether you're looking to build AI-driven tools, automate data workflows, or leverage the latest in LLM technology, this course will guide you through every step.Prepare yourself for a hands-on, interactive experience that will transform your understanding of LangChain. With our simple, three-step approach-Why, What, and How-you'll learn to apply LangChain to solve real-world challenges. Who This Course Is For:New to LLM/GenAI but from the IT Industry: If you're familiar with the IT world but new to Generative AI and Large Language Models, we'll start from the ground up and help you build advanced applications by the end.Career Transitioners: If you're transitioning into IT from another field and want to get into Generative AI, this course will give you a solid foundation with practical skills to launch your career.Learners with Some GenAI Experience: For those who have dabbled in GenAI and want to learn LangChain in depth, this course will take your understanding and skills to the next level.Experienced AI Developers: If you've built GenAI applications before but have been piecing things together from scattered resources, this course will offer a structured, comprehensive guide to building AI apps the right way.What You Will LearnThrough practical projects, you'll master essential skills in LangChain and the LangChain ecosystem. Here's what we'll cover:Understanding LLM and AI BasicsStart with AI fundamentals, covering LLMs, their workings, prompts, tokens, and more-setting a strong foundation.Getting Started with LangChainSet up your environment, write your first GenAI code, and explore LangChain's benefits.ModelsLearn about chat models, LLMs, token usage, and work on hands-on projects.Prompts & Output ParsersMaster prompt creation and output parsing, including handling JSON for real-world use case.Streamlit for AI AppsBuild a user-friendly UI for your AI apps with Streamlit.ChainsExplore LangChain chains and Runnables and built apps like video analyzer, resume enhancer, and email generator.MemoryLearn to manage memory in LangChain, enhancing conversation flow in apps.Prompt EngineeringDive deeper into advanced prompt engineering techniques.Real-World LLM Use CasesExplore practical LLM applications and understand where GenAI adds the most value.RAG: Working with Your DataImplement Retrieval-Augmented Generation, creating tools like a QA bot, summarizer, and comparison tool.LangSmith: Debugging and EvaluationLearn to debug and observe LangChain apps using LangSmith.Advanced RAGExpand on RAG with multi-query and indexing, building more sophisticated applications.CallbacksImplement callbacks to optimize and monitor application workflows.Deploy and Share AI AppsDeploy your AI apps on Streamlit Cloud and Hugging Face Spaces, sharing your projects seamlessly.Course Structure and BenefitsMajor benefit of this course is its simplicity-complex concepts are broken down into easy-to-understand explanations, making both theory and practical applications accessible for all learners.Project-Based Learning: Each section includes interactive projects, allowing you to apply concepts directly to real-world scenarios.Structured Learning Path: Topics are organized sequentially, moving from foundational to advanced topics for a comprehensive understanding.By the End of This Course, You Will Be Able To:Build, debug, and deploy LangChain applications tailored to solve real-world problems.Implement effective prompt engineering techniques and handle complex workflows with agents.Create dynamic, user-friendly UIs with Streamlit and manage context in AI applications using memory.Optimize your applications with LangSmith and deploy your solutions confidently.Join us and start building powerful AI apps today!
