Agents Academy

Yes, 100% free. No sign-up, no credit card. All modules, lessons, and quizzes are immediately accessible. Progress saves locally in your browser.

AI Agents are autonomous software systems that use large language models (LLMs) to perceive their environment, make decisions, and take actions to accomplish goals — going beyond simple chatbots by maintaining state, using tools, and operating in loops.

The course covers agent fundamentals, the ReAct loop, tool calling, LangGraph state machines, multi-agent swarms, RAG (Retrieval-Augmented Generation), vector databases, MCP integration, A2A protocol, agent observability, production deployment patterns, and real-world case studies.

LangGraph is a framework for building stateful, multi-step AI agent workflows as directed graphs. It enables complex agent architectures with cycles, branching, and human-in-the-loop patterns — essential for production-grade autonomous systems.

Basic familiarity with Python or JavaScript is helpful but not required. The course starts from absolute fundamentals and progressively advances to expert topics like multi-agent orchestration and production deployment.

Agent-to-Agent (A2A) is Google's open protocol for AI agents to communicate, collaborate, and delegate tasks to each other across different platforms and vendors — enabling true multi-agent interoperability.