Adversarial AI: Attacking, Defending & Governing ML Systems

As AI becomes central to cybersecurity defence, attackers are increasingly targeting the AI systems themselves. Model poisoning, adversarial inputs, backdoor exploits, and model stealing are active threats — and most security teams are unprepared to detect or defend against them. This course gives you the knowledge and practical strategies to secure ML systems from the inside out. You'll examine how ML systems are manipulated through adversarial inputs, poisoning attacks, and threat models across real-world use cases including malware detection and fraud analytics. You'll then explore advanced