trusted with, where it fails, and how to keep human judgment in charge. This course teaches that skill to any professional, in any role. No technical background is required, and no AI expertise is assumed: this is a course for the professional, not the engineer.
AI is already part of everyday work — drafting, analysing, deciding, creating. It is powerful, and it is confidently wrong often enough to matter. It can be biased, it can leak what it’s told, and it fails silently. The responsibility for the results stays with the person using it. This course is not about memorizing AI terminology or regulations; it is about developing good judgment when working with AI — judgment that stays useful no matter how the technology changes.
What the course covers
Across eleven modules, the course covers the full landscape of responsible AI:
- Foundations of responsible AI — what responsible AI means, and the 12 principles that define it
- How AI actually behaves — capabilities, limitations, and why confident is not the same as correct
- Bias and fairness — where bias enters AI systems and what fairness requires in practice
- Truth, accuracy and transparency — verifying AI output, transparency versus explainability, and a world where seeing is no longer believing
- Privacy — what AI systems collect, infer and remember, and how to protect personal data when using AI
