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所在平台: Udemy |
课程主页: https://www.udemy.com/course/spring-ai-for-beginners-build-genai-llm-apps-in-easy-steps/
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课程名称：初学者的春季人工智能：轻松构建生成式AI大模型应用 课程概述： 欢迎来到初学者的春季人工智能课程！本课程旨在提供一个循序渐进的引导，以帮助您从基础到更高级的概念了解春季AI。不论您是完全的新手还是有些AI经验，本课程将助您理解并利用春季AI的力量构建智能应用。 课程目标： - 渐进学习：通过清晰简洁的指导，逐步学习春季AI的基础和高级主题。 - 全面理解：理解春季AI为何是构建AI应用的强大工具，以及它如何简化语言模型的整合。 - 实践经验：获得春季AI的关键功能如提示模板、链、代理、文档加载器、输出解析器和模型类的实际经验。 您将学到： - 春季AI简介：了解春季AI的基础和核心概念。 - 春季AI的构建模块：学习提示模板、链、代理、文档加载器、输出解析器和模型类。 - 创建AI应用：了解这些功能如何结合起来构建智能灵活的应用。 - 实际编码：书写和运行示例代码，亲身感受春季AI开发的过程。 课程结构： - 简明章节：每个章节专注于春季AI编程中的特定主题，确保您深入理解每个概念。 - 互动学习：跟随提供的示例代码进行编程训练，以巩固您的学习并提高技能。 课程结束时，您将能够： - 了解春季AI及其如何简化在应用中使用大语言模型（LLMs）。 - 在Spring Boot应用中使用OpenAI LLMs。 - 在Spring Boot应用中使用开放源代码的LLMs（如Mistral、Gemma）。 - 使用OLLAMA在本地机器上运行开放源代码的LLMs。 - 使用提示模板重用和构建动态提示，了解如何维护聊天历史。 - 理解嵌入（embeddings）的概念，并使用嵌入模型找到文本相似性。 - 理解向量存储（Vector Store）的概念，并用其存储和检索嵌入。 - 理解检索增强生成（Retrieval Augmented Generation，RAG）的过程，并实现RAG以简单步骤使用自己的数据与LLMs。 - 使用多模态模型分析图像。 - 使用Thymeleaf和春季AI构建多个LLM应用。 所有内容均以简单易懂的步骤进行讲解。
Welcome to Spring AI for Beginners!This course is designed to provide a gentle, step-by-step introduction to Spring AI, guiding youfrom the basics to more advanced concepts. Whether you're a complete novice or have someexperience with AI, this course will help you understand and leverage the power of Spring AI forbuilding AI-powered applications.Course Goals:- Gradual Learning: Learn Spring AI gradually from basic to advanced topics with clear andconcise instructions.- Comprehensive Understanding: Understand why Spring AI is a powerful tool for building AIapplications and how it simplifies the integration of language models into your projects.- Hands-On Experience: Gain practical experience with essential Spring AI features such asprompt templates, chains, agents, document loaders, output parsers, and model classes.What You Will Learn:- Introduction to Spring AI: Get started with the basics of Spring AI and understand its coreconcepts.- Building Blocks of Spring AI: Learn about prompt templates, chains, agents, document loaders,output parsers, and model classes.- Creating AI Applications: See how these features come together to create a smart and flexible- Practical Coding: Write and run code examples to get a hands-on sense of how Spring AIdevelopment looks like.Course Structure:- Concise Chapters: Each chapter focuses on a specific topic in Spring AI programming,ensuring you gain a deep understanding of each concept.- Interactive Learning: Code along with the examples provided to reinforce your learning and buildyour skills.By the end of this course, you will:Learn what Spring AI is how it simplifies using LLMs in our applicationsUse OpenAI LLMs in a Spring Boot applicationUse Open Source LLMs like Mistral,Gemma in a Spring Boot applicationRun Open Source LLMs on your local machine using OLLAMAUse PromptTemplates to reuse and build dynamic prompts Learn why and how to maintain Chat HistoryLearn what embeddings are and use the Embeddings Model to find text SimilarityUnderstand what a Vector Store is and use it to store and retrieve EmbeddingsUnderstand the process of Retrieval Augmented Generation(RAG) Implement (RAG) to use our own data with LLMs in simple stepsAnalyze images using Multi Modal ModelsBuild multiple LLM APPs using Thymeleaf and Spring AIAll in simple steps
