Adversarial AI: Attacking, Defending & Governing ML Systems
Completed by Gopika Chandran A J
October 9, 2026
10 hours (approximately)
Gopika Chandran A J's account is verified. Coursera certifies their successful completion of Adversarial AI: Attacking, Defending & Governing ML Systems
What you will learn
Analyse adversarial attack vectors targeting ML systems including poisoning, model stealing, & backdoor exploits, and assess their operational impact
Design & implement layered technical defences using differential privacy, guardrail protection, & secure algorithm design to maintain model integrity
Plan and conduct AI security testing using red, purple, and blue teaming approaches to validate ML model robustness under adversarial conditions
Evaluate responsible AI governance frameworks and regulatory requirements to ensure AI systems are ethical, fair, and compliant
Skills you will gain
- Category: AI Security
- Category: Cybersecurity
- Category: Data Governance
- Category: Penetration Testing
- Category: Governance
- Category: Security Testing
- Category: Cyber Governance
- Category: Information Privacy
- Category: Cyber Attacks
- Category: Artificial Intelligence
- Category: Responsible AI
- Category: Data Ethics

