Program Curriculum and Learning Path: Mastering AI Agents Certification
Table of contents
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The Journey Ahead
This program focuses on designing and evaluating multi-agent AI systems.
You’ll learn how to build systems where multiple agents specialize, coordinate, use tools, and make decisions together — and how to evaluate whether those systems are behaving as intended.
This lesson gives you a high-level view of how the curriculum is organized and how the pieces fit together. If you want the details, jump directly to the curriculum map below.
Program Structure
The program is organized into five units, each focused on a distinct capability required to build effective multi-agent systems.
- Unit 1 introduces agentic systems as an evolution of workflows, using LangGraph to model state, control flow, and agent behavior.
- Unit 2 focuses on tool use and integration, teaching how agents interact with external systems and how MCP enables scalable, standardized tool access.
- Unit 3 shifts to multi-agent architecture, covering how to design, assign, and coordinate multiple specialized agents in a single system.
- Unit 4 is dedicated to evaluation, exploring how to test, measure, and validate agentic and multi-agent behavior beyond traditional testing methods.
- Unit 5 brings everything together in a capstone project, where you design and submit a complete multi-agent system.
Each unit builds directly on the previous one, introducing complexity only when it becomes necessary.
What You’ll Build
The program culminates in a capstone project where you design and implement a multi-agent system that solves a meaningful problem.
You’ll be guided through:
- defining the system architecture,
- implementing agent collaboration and tool use,
- and evaluating system behavior and coordination.
As with the previous program, the capstone is supported by:
- a clear project definition,
- a starter template to reduce setup friction,
- and explicit submission guidance.
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