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所在平台: Udemy |
课程主页: https://www.udemy.com/course/generative-ai-with-ai-agents-mcp-for-developers/
课程评论：没有评论
课程名称：开发者的生成式人工智能与AI代理及MCP课程 课程概述：本实操课程将教您如何构建专业级的生成式人工智能应用和智能自主AI代理，采用模型上下文协议（MCP）和现代大语言模型（LLM）框架。无论您是人工智能初学者还是经验丰富的开发者，该课程将一步步带您了解现代生成式人工智能应用所需的工具、策略和架构。 您将学习的内容包括： - 生成式人工智能的介绍及其在现代开发中的角色 - 大语言模型（LLMs）的基础与如何为智能应用赋能 - 生成式AI应用架构基础 - 理解生成式AI应用的核心组件 - 先进的生成式AI应用架构，适用于可扩展和模块化系统 - 如何应用增强检索生成（RAG）技术以提升响应效果 - 选择合适的编排框架来构建基于LLM的应用 - LangChain - LLM编排的现代框架 - LangChain表达语言（LCEL） - 使用简洁的声明性语法构建AI流程 - 深入了解LangChain生态系统中的代理、工具、记忆和链 - 掌握提示工程 - 学习为LLM设计最佳提示 - 初级生成式AI应用 - 构建基本的AI工具和助手 - LlamaIndex - RAG和LLM应用编排的LangChain替代方案 - 大语言模型操作（LLMOps） - 管理和监控LLM应用 - 中级生成式AI应用 - 构建具有记忆、工具和检索的系统 - 开发多模态生成式AI应用（整合文本、图像、音频） - 使用编排框架构建和部署AI代理及多代理系统 - 高级（专业级）生成式AI应用 - 实时、可扩展、生产就绪的系统 - 生成式AI的持续集成/持续部署（CI/CD） - 通过自动化管道部署您的生成式AI应用 - 理解和实施模型上下文协议（MCP） - 实操项目 - 从AI助手到自主代理以及基于RAG的应用 - 为特定领域用例和更好性能微调LLM 该课程将为您提供创建和管理生成式AI应用所需的全面知识和实战经验。
This hands-on course teaches you how to build professional level Generative AI Application, intelligent, autonomous AI Agents using MCP (Model Context Protocol) and modern LLM frameworks.Whether you're an AI beginner or an experienced developer, this course will take you step-by-step through the tools, strategies, and architectures that power modern GenAI applications.What You'll Learn:- Introduction to Generative AI and its role in modern development- Introduction to Large Language Models (LLMs) and how they power intelligent applications- Generative AI Architecture Basics - understand the core components of a Gen AI application- Advanced Gen AI Application Architecture for scalable and modular systems- How to apply the Retrieval-Augmented Generation (RAG) technique for enhanced responses- Choosing the Right Orchestration Framework for building LLM-powered apps- LangChain - A modern framework for LLM orchestration- LangChain Expression Language (LCEL) - Build AI flows with clean, declarative syntax- Deep dive into the LangChain Ecosystem for agents, tools, memory, and chains- Mastering Prompt Engineering - Learn to craft optimal prompts for LLMs- Level 1 Gen AI Applications - Basic AI-powered tools and assistants- LlamaIndex - An alternative to LangChain for RAG and LLM app orchestration- LLMOps (Large Language Model Operations) - Manage and monitor LLM Apps- Level 2 Gen AI Applications - Build intermediate systems with memory, tools, and retrieval- Develop Multimodal Gen AI Applications (text, image, audio integration)- Build and deploy AI Agents & Multi-Agent Systems using orchestration frameworks- Level 3 (Professional) Gen AI Applications - Real-time, scalable, production-ready systems- CI/CD for Gen AI - Deploy your Gen AI apps with automated pipelines- Understand and implement MCP (Model Context Protocol) - Hands-on Projects - From AI assistants to autonomous agents and RAG-powered apps- Fine-tuning LLMs for domain-specific use cases and better performance
