The Complete Agentic AI Bootcamp

About this course

This course contains the use of artificial intelligence.

Most AI courses stop at prompting a chatbot. This one goes further and teaches you how to design, build, and ship real agentic systems, the kind that plan, use tools, coordinate with other agents, and know when to bring a human into the loop.

You start with the fundamentals: the observe, think, act loop that powers every modern agent, and how to turn any function into a reliable tool an LLM can call. From there you move into LangGraph, learning how to build stateful workflows with branching logic, checkpoints, and human in the loop review steps that pause a workflow for approval before it continues.

Next you move into multi-agent systems with CrewAI, where you learn to design specialized agents that collaborate on a single task instead of relying on one generalist model to do everything. You will explore sequential and hierarchical processes, tool sharing, and delegation between agents.

The course then covers the protocol layer that ties everything together. MCP for connecting agents to tools and data, and A2A for agent to agent communication and discovery, along with AG-UI for connecting agents to user facing interfaces. You will understand why these protocols exist, what problem each one solves, and how they fit together in a real system.

Throughout, the focus stays on memory and state design, how agents remember across sessions and recover from failure, the Agent Development Lifecycle, and evaluation practices that keep agent behavior reliable rather than unpredictable.

Every concept is taught through hands on projects built with real, verified APIs and current documentation, not toy examples. You will write and explain working code yourself, cell by cell, so you understand not just what the code does but why it is built that way.

This course is built for developers who already know their way around Python and LLM APIs and want to go from writing prompts to engineering agents that actually hold up in producti

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