Architect autonomous AI agents, multi-agent swarms, tool-calling reasoning loops, and Model Context Protocol (MCP) systems.
Step into the frontier of autonomous intelligence. Learn how to architect goal-driven AI agents capable of planning, reflection, tool calling, memory management, and multi-agent collaboration using LangGraph, CrewAI, AutoGen, and the Model Context Protocol (MCP).
12 weeks · 48 guided hours · 4 hours / week · ₹9,999
Syllabus
- Autonomous Agent Architectures & ReAct Loops: Understanding prompt engineering for reasoning, action cycles, and observation loops.
- Tool Integration & Model Context Protocol (MCP): Connecting agents to external APIs, databases, shells, and standardized MCP servers.
- Multi-Agent Systems & State Graphs: Building hierarchical and collaborative multi-agent teams using LangGraph state machines.
- Enterprise Autonomous Agent Capstone: Deploying a production-grade autonomous research and coding agent team with persistent memory.
What you will learn
- Agentic loop patterns: ReAct, Plan-and-Solve, Reflection, and Tree-of-Thought
- Dynamic tool calling and function execution with strict schemas
- Model Context Protocol (MCP) server & client architecture
- Multi-agent orchestration and role-based swarms with LangGraph and CrewAI
- Persistent agent memory systems using vector databases and state graphs
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