📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of AI Policy Labs Regulation in Practice, from foundations to a certified capstone project.
Outline
Explore the risks and public interest in AI regulation • Understand core concepts – risk-based regulation, accountability, transparency • Categorize AI use cases and risk levels
Outline
Analyze the EU AI Act – provisions, risk tiers, and obligations • Examine the U.S. AI Strategy – Executive Orders, NIST AI RMF, FTC Guidance • Compare global regulatory approaches: risk, rights, and enforcement models
Outline
Classify AI systems and map use cases • Implement compliance requirements for high-risk systems • Assign roles and accountability: DPOs, risk officers, and AI governance leads
Outline
Conduct impact assessments (AI, human rights, algorithmic, environmental) • Perform conformity assessments and post-market monitoring • Develop supplier and third-party due diligence
Outline
Set up regulatory role-play (company, regulator, public) • Enforce the EU AI Act – mock review and assessment • Simulate U.S. risk management strategy
Outline
Explore sandbox models and experimental regulation • Engage in public participation and governance • Build regulatory foresight into AI strategy
Earn government-registered certification in AI Policy Labs Regulation in Practice
e-Certificate and e-Marksheet issued on successful completion.
