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所在平台: Udemy |
课程主页: https://www.udemy.com/course/complete-master-class-on-agent-to-agent-a2a-protocol/
课程评论：没有评论
**课程名称：** Agent2Agent (A2A) 协议完整大师班 **课程概述：** 本课程专为 AI 爱好者设计，深入讲解 Google 的 Agent2Agent (A2A) 协议。 A2A 协议正在改变 AI 通信的格局，它支持构建互连的 Agent 生态系统，使 AI Agent 能够实时发现、理解和协作。 A2A 由 Google 支持，并迅速发展成为互操作性 AI 系统的核心标准。 **您将学到：** * A2A 协议的基础知识和高级通信流程。 * 通过官方 A2A 文档的示例进行实际操作。 * 多个真实 Agent 实现和现场演示。 * 如何构建简单 Agent、流式响应 Agent 和受保护 Agent 卡。 * 使用 Gemini Flash 和工具调用实现 A2A 多 Agent 系统。 * 使用 LangGraph 和 Crew AI 实现 A2A Agent。 * 使用 Google ADK 实现 A2A Client。 * 使用 Gradio 构建浏览器 UI 以实现多 Agent 交互。 * A2A 协议规范的详细解读。 * 开发环境的搭建和配置。 **为何参加此课程：** * **实际技能：** 了解 A2A 如何融入未来 Agent 系统实现协议及多 Agent AI 系统。 * **实践项目：** 设置客户端-服务器 Agent 对，执行通信流程、安全 Agent 通信、支持工具调用的多 Agent A2A 协议。 * **简明解释：** 将技术规范分解为易于理解的实践步骤，并附带技术实现演示。 * **技能前瞻：** 在这个快速发展的领域掌握 Agent 到 Agent 协议和多 Agent 系统开发相关的专业知识。 **课程内容亮点（更新）：** * **2025年6月23日：** 新增知识检测测验，新增真实世界多 Agent A2A 系统用例演示视频。 * **2025年6月24日：** 新增使用 A2A 服务器实现 LangGraph Agent，新增使用 A2A 服务器实现 Crew AI Agent。 * **2025年6月25日：** 新增使用 A2A Client 实现 Google ADK Orchestrate Agent，新增使用 Gradio 构建多 Agent A2A 浏览器 UI，新增 LangGraph、Google ADK、Crew AI Agent 集成的完整 A2A 多远程 Agent 演示。 **课程目标：** 学完本课程后，您将具备在真实 Agent 系统中实现 A2A 协议的实践经验，能够创建从简单 Agent 到更复杂的、支持流式响应和跨多个交互保持上下文的 LLM 驱动对话 Agent。 **课程面向人群：** * 想了解 A2A 协议工作原理并希望自行构建的任何人。 * 希望使用标准化 A2A 协议构建互操作性 AI Agent 系统的软件工程师和开发者。 * 希望将其知识从模型构建扩展到 Agent 架构的 AI/ML 工程师。 * 需要了解 Agent 系统如何协同工作的技术产品经理。 * 正在规划需要多个 Agent 系统之间协作的 AI 生态系统的解决方案架构师。 * 评估连接 AI Agent 网络实现策略的技术团队领导者。 **课程包含：** * 3 小时以上视频讲座 * 可下载的代码和资源 * 终身访问权限 * 结业证书 * 讲师 Q&A 支持 **先修要求：** * 具备 Python 基础知识。 * 在您的系统上安装 Python 3.12+。 * 愿意学习前沿知识。
DescriptionWelcome to the most comprehensive course on Google's Agent2Agent (A2A) Protocol for AI Enthusiasts.The Agent-to-Agent (A2A) Protocol is changing the landscape of AI communication. Instead of building standalone agents that operate in isolation, A2A enables the development of interconnected agent ecosystems-where AI agents can discover, understand, and collaborate with one another in real time. Backed by Google and rapidly gaining momentum, A2A is emerging as the core standard for interoperable AI systems.What You'll Learn in This Technical Deep DiveIn this course, you'll go beyond the theory and into practical implementation. Starting with the fundamentals of the A2A Protocol, you'll progress to advanced agent communication flows, working directly with examples inspired by the official A2A documentation. You'll explore multiple real-world agent implementations and step through live demos that clearly explain each concept, helping you build a strong foundation and the confidence to apply A2A in your own projects.Update: Jun 23 , 2025Added Quizzes for checking gained Knowledge.Added Demo video of Real world Multi A2A agent Systems use caseUpdate: Jun 24 , 2025Added Lang graph agent implementation using A2A Server.Added Crew Ai agent implementation using A2A Server.Update: Jun 25 , 2025Added Google ADK Orchestrate Agent implementation using A2A Client.Added Browser UI for Multi A2A agent suing Gradio.Added Full Demo of Final A2A multi remote agents with Lang graph. Google ADK, Crew AI agentsWhy Take This Course?Real-World Skills: Learn how A2A fits into future Agent system Implementation protocols and the larger Multi agent AI SystemsHands-On Projects: Set up client-server agent to agent pairs and execute communication flow, Secured Agent Communication, Multi agent with Tool calling in A2A Protocol.Simple Explanations: Break down technical specs into digestible, practical steps followed with Technical Implementation DemoFuture-Proof Your Skills: Gain expertise in a fast-growing field relevant to Agent to Agent Protocol , Multi agent system development.Section 1: Introduction to A2A CourseCourse OutlineWhy You should Learn A2AGet to Know your InstructorNotes about getting most out of this CourseWhat to do if you need help while following this courseSection 2: Introduction to AI Agents and A2A ProtocolData Science in 3 MinutesLLM OverviewA Little Secret: Quick Trick to Grasp All AI Concepts EasilyWhat is Tool or Function CallingWhat is AI AgentsSection 3: Overview of A2A ProtocolA2A in One SentenceWhat is MCP and How MCP WorksA2A Detailed OverviewA2A and MCP in Big Picture of Agentic AI SystemsMulti-Agent System using A2A ProtocolSection 4: A2A Protocol Basic ConceptsA2A Basics - Core ActorsA2A Basics - Simple A2A Communication FlowA2A Basics - Agent Cards Explained in DetailA2A Basics - Agent Discovery MechanismsSection 5: A2A Advanced Concepts - Communication ProtocolsA2A: Core Objects & EventsJSON-RPC Methods in A2A ProtocolAgent-to-Agent Web Protocols (HTTP, POST, SSE, JSON-RPC)A2A Authentication MechanismsA2A Detailed Communication FlowSection 6: A2A Protocol SpecificationLogical Concept vs. Technical ImplementationA2A Protocol Specification - Agent DiscoveryAgent Card Resolver - SDK Implementation(Optional) Why Covering All Specification in Theory Isn't IdealSection 7: Setting Up Development EnvironmentInstall Code Editor (Visual Studio Code)Install Python (Windows/Mac)Install Pip (Windows/Mac)Install UV (Windows/Mac)Starlette ASGI Service - API Host IntroductionUvicorn Server SetupSection 8: Building a Simple A2A AgentSimple A2A Agent - Architecture DiagramA2A Specification ImplementationPython Project StructureSetting Up and Running the Simple A2A AgentCode Walkthrough and DemoClosing NotesSection 9: Implementing an A2A Streaming AgentStreaming Response IntroductionPython Specification DiagramRunning the Streaming Agent DemoCode Walkthrough and DemoSection 10: Implementing an A2A Protected Agent CardQuick Demo of Protected Agent CardA2A Specification for Protected CardsPython Specification DiagramSetup and Run the Protected Agent DemoCode Walkthrough and DemoClosing NotesSection 11: Advanced Implementation - Multi-Agent with Gemini Flash & Tool CallingArchitecture DiagramQuick DemoPython Program SpecificationTooling Support for AI AgentsTool Calling with Supported LLMGetting a Gemini API KeySetting up Gemini API Key in.envProgram File StructureCode Walkthrough - A2A ClientCode Walkthrough - Server Config & Main FileCode Walkthrough - Agent Executor (Middleman)Code Walkthrough - Remote Agent & Tool ImplementationSetting Up and Running the DemoFinal Demo & Output ReviewBy the end of this course, you'll have practical experience implementing the A2A Protocol in real agent systems, creating both simple agents to More complex LLM-powered conversational agents that can stream responses and maintain context across multiple interactions.All examples and implementations are based official A2A Protocol documentation from Google and the reference code available to download with course Materials, ensuring you're learning the accurate implementation techniques.Join thousands of developers who are building the future of interoperable AI with Google's Agent 2 Agent Protocol. Enroll now and start creating agents that don't just work in isolation, but form part of a connected, collaborative AI ecosystem.Who this course is for:Any One Who want to Know How A2A protocol works and Want to build one by yourself.Software Engineers and Developers who want to build interoperable AI agent systems using standardized A2A protocolsAI/ML Engineers looking to extend their knowledge beyond model building to creating agent architecturesTechnical Product Managers who need to understand how agent systems can be designed to work togetherSolution Architects planning AI ecosystems that require collaboration between multiple agent systemsTechnical Team Leaders who are evaluating implementation strategies for connected AI agent networksCourse Includes3+ hours of video lecturesDownloadable code and resourcesLifetime accessCertificate of completionQ & A support from the instructorRequirementsBasic knowledge of PythonPython 3.12+ installed on your systemA willingness to learn something cutting-edge!Get Started TodayJoin the course and become one of the early developers skilled in implementing decentralized, secure, agent-to-agent communication.Start building the future of AI and A2A Agents , one agent at a time.
