Navigating Multi-Agent Communication Protocols is an intermediate-level course designed for AI engineers and system architects who need to build sophisticated multi-agent systems where effective communication and coordination are critical. In today's AI landscape, isolated agents are obsolete—success depends on seamless collaboration between multiple intelligent agents working toward shared objectives.
Agentic AI Protocols (MCP, A2A, ACP)
只需 199 美元（原价 399 美元）即可通过 Coursera Plus 学习更高水平的技能。立即节省
您将获得的技能
要了解的详细信息
了解顶级公司的员工如何掌握热门技能
该课程共有3个模块
In this foundational lesson, learners will explore the architecture and components of the Multi-Agent Communication Protocol (MCP), examining how it facilitates effective information exchange between AI agents. Through real-world examples from Anthropic's implementation and industry case studies, learners will analyze MCP's structural elements, understand its role in standardizing agent communication, and practice identifying optimal scenarios for MCP deployment.
涵盖的内容
3个视频2篇阅读材料1个作业
This lesson focuses on Agent-to-Agent (A2A) protocols and their application in coordinating tasks among AI agents. Learners will examine Google's implementation of A2A in autonomous systems, understand the strategic differences between A2A and MCP, and practice designing coordination mechanisms for complex multi-agent tasks. Through hands-on exercises and real-world case studies, learners will develop skills in task distribution, coordination patterns, and performance optimization in A2A environments.
涵盖的内容
3个视频1篇阅读材料1个作业
In this final lesson, learners will examine the Agent Collaboration Protocol (ACP) and its application in enterprise environments for collaborative execution. They'll analyze IBM's implementation approach, understand ACP's unique strengths in managing complex collaborative workflows, and develop strategies for optimizing collaborative execution in diverse AI systems. The lesson culminates with a comprehensive capstone project where learners design a multi-protocol implementation plan, and a graded assessment that tests their understanding across all three protocols.
涵盖的内容
3个视频2篇阅读材料3个作业
位教师
提供方
从 Machine Learning 浏览更多内容
状态：预览Fractal Analytics
状态：预览Vanderbilt University
状态：预览Coursera
状态：预览
人们为什么选择 Coursera 来帮助自己实现职业发展
Felipe M.
自 2018开始学习的学生
''能够按照自己的速度和节奏学习课程是一次很棒的经历。只要符合自己的时间表和心情，我就可以学习。'
Jennifer J.
自 2020开始学习的学生
''我直接将从课程中学到的概念和技能应用到一个令人兴奋的新工作项目中。'
Larry W.
自 2021开始学习的学生
''如果我的大学不提供我需要的主题课程，Coursera 便是最好的去处之一。'
Chaitanya A.
''学习不仅仅是在工作中做的更好：它远不止于此。Coursera 让我无限制地学习。'
常见问题
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
更多问题
提供助学金，
¹ 本课程的部分作业采用 AI 评分。对于这些作业，将根据 Coursera 隐私声明使用您的数据。