What the course covers.
- Module 1
Foundations of AI Safety & Ethics
Learners begin by exploring key concepts in AI safety and ethics, including bias, fairness, transparency, and accountability. The module covers regulatory frameworks, ethical AI guidelines, and real-world case studies, helping participants understand how to design AI systems responsibly and avoid common pitfalls.
- Module 2
Secure & Robust AI Systems
This module focuses on building AI models that are resilient to attacks and failures. Learners explore adversarial examples, model robustness, secure data handling, and threat mitigation strategies. Hands-on exercises involve testing and strengthening models to ensure reliability and security in critical applications.
- Module 3
Practical Implementation & Compliance
Learners apply ethical and security principles to real-world AI projects. The module covers model auditing, fairness evaluation, secure deployment, and compliance with industry standards and regulations. Participants gain the skills to design AI systems that are not only effective but also trustworthy, safe, and ethically aligned.
