Agentic AI Protocols (MCP, A2A, ACP)

Coursera Courses ↗ · Coursera

Open Course on Coursera

Free to audit · Opens on Coursera

Agentic AI Protocols (MCP, A2A, ACP)

Coursera · Intermediate ·🤖 AI Agents & Automation ·1mo ago
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. This course provides comprehensive coverage of three essential communication protocols: Multi-Agent Communication Protocol (MCP) for standardized communication, Agent-to-Agent (A2A) for dynamic task coordination, and Agent Collaboration Protocol (ACP) for complex workflow orchestration. Through real-world case studies from organizations like Anthropic, Google, and IBM, hands-on implementation exercises, and practical design challenges, you'll learn to strategically select and integrate these protocols to solve complex coordination problems. Whether you're building autonomous systems, enterprise AI solutions, or collaborative AI applications, this course equips you with the knowledge and skills to transform chaotic agent interactions into orchestrated, efficient collaborations that deliver measurable business value.
Watch on Coursera ↗ (saves to browser)
Sign in to unlock AI tutor explanation · ⚡30

Related AI Lessons

Browse public service handles at biznode.1bz.biz/handles.php — discover AI bots offering legal, medical, finance, consulting...
Explore AI-powered public service handles at 1BZ BizNode, offering various services like legal, medical, and finance consulting
Dev.to AI
Build a Profitable AI Agent with LangChain: A Step-by-Step Tutorial
Learn to build a profitable AI agent using LangChain by following a step-by-step tutorial and earn money by automating tasks and providing valuable services.
Dev.to AI
Teaching My AI Agents to Push Back: Why I Built RoBrain
Learn how to build AI agents that can push back and improve solo coding with auto-memory features
Dev.to · Adeline
Not so locked in any more
Learn how coding agents can facilitate rewriting legacy code, making it easier to switch programming languages or frameworks
Simon Willison's Blog
Up next
Deploying AI Agents: LLMs, LangGraph, and Production APIs
Coursera
Watch →