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Library / Artificial Intelligence

Agentic AI & Multi-Agent Masterclass: Build, Test & Secure

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About this course

This course contains the use of artificial intelligence

An AI agent does not only answer. It looks things up, calculates, opens tickets and asks a person before anything risky. A team of agents can split a job, check each other, and finish work no single prompt could. That power is also the risk: an agent that can act can loop forever, spend your budget, or be tricked by one hidden sentence. This course teaches you to build agents that are useful, measured and safe, one small file at a time.

Every lecture reads real code line by line, then runs it and reads the real output. Nothing is a paraphrase: the logs on screen are the logs the code printed.

You build:

  • Your first AI agent: a research helper with a search tool, a calculator, memory with a token budget and a step limit.
  • A multi-agent team: a supervisor that hands work to a researcher, an analyst and a reviewer through a shared notebook.
  • Agentic workflows in LangGraph: routing, loops with a hard limit, and a refund workflow that pauses for a manager's approval and resumes later.
  • An MCP tool server: tools shared by every agent, with checks at the door for who may call, what goes in and what comes out.

A web service: the agent behind FastAPI, with settings and secrets, searchable JSON logs, trace ids, an audit log, retries, a rate limit and a token budget.

An evaluation suite: an answer key, graders and a release gate that caught a one-line prompt change dropping the score from 10/10 to 2/10.

Offline tests: a fake model and fake tools that check the loop in a fraction of a second, for free.

Security labs: a deliberately vulnerable agent, four defenses, and the same attacks run against both, plus how to meet a tool server you did not write. Attacks run only against a scripted model, never a real provider.

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