Designed for professionals, developers, and decision-makers to lead ethical AI governance and ensure regulatory compliance. Topics include algorithmic transparency, explainable AI (XAI), governance frameworks, and regulatory impact analysis under GDPR and the EU AI Act. Emphasis on case studies and scenarios. Learners audit models for compliance/fairness, design ethically aligned solutions, and assess risks from automation, data use, and AI-driven decisions.

Self-Assessment Quizzes; Practical Lab Exercises; Assignments; Essays/Reports; Knowledge Checks; Final Exam (Online); Case Studies; Projects

Lectures; Videos; Hands on Labs; Practical Labs; Case Studies; Live Code Demos; Code Reviews; Literature Reading

Assess complex AI systems for ethical, legal and social implications; develop strategies for ethical AI governance (internal guidelines, oversight committees, integration into corporate strategy); interpret/apply AI ethics regulations and communicate compliance; lead multidisciplinary teams and ethics reviews; collaborate across disciplines and act as an ethics ambassador.

Deep understanding of AI ethics frameworks and regulations; Ability to develop organisational guidelines/policies/governance strategies; Proficiency in advanced ethical audits and impact assessments on AI systems

Ethical leadership and responsible management; Strategic communication and high-level negotiation; Strategic approaches to AI implementation