Turn requirements into working governance
Learn how to run the practical work: build controls, evidence, governance routines and a remediation plan using the AI Act Ready tool.
Run a discovery session that produces a usable, evidence-oriented AI inventory.
Build a practical AI risk process aligned with the AIMS and client objectives.
Identify affected people and impacts before determining the depth of assessment required.
Turn data-quality obligations into evidence and controls.
Design oversight that works in the real workflow rather than only on paper.
Create an evidence structure that lets a reviewer understand the system and the decisions behind it.
Control AI risk that enters through vendors and upstream models.
Move from a policy statement to a tested, visible disclosure control.
Build the feedback loop after deployment.
Select and implement practical AIMS controls based on organisational risk.
Prove the AIMS is monitored and improved by management.
Complete the simulated client engagement and produce the required evidence pack.
The goal is not to memorise wording. It is to show that you can reason, document assumptions, ask for evidence and know when to escalate.
Work through the stage-specific scenarios after completing the modules. Answers include explanations and source-basis notes.
Start stage knowledge check