Programme Parameters
Advanced Postgrad
3 Weeks (30 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
AI Policy Labs: Regulation in Practice is a simulation-driven, policy-maker-focused program designed to translate ethical principles and legal frameworks into enforceable AI regulation. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
AI Policy Labs: Regulation in Practice is a simulation-driven, policy-maker-focused program designed to translate ethical principles and legal frameworks into enforceable AI regulation.
📋 Course Objectives
1. Put AI Enablement techniques to work on real datasets and case studies.
2. Build a defensible project you can showcase to supervisors, reviewers, or employers.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in AI Enablement
• R&D engineers and working professionals applying AI Enablement in industry
• Academics and educators building research or teaching capacity in AI Enablement
🚀 Key Learning Outcomes
• A portfolio-grade AI Enablement deliverable you can defend and extend.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Foundations of AI Regulation
Explore the risks and public interest in AI regulation • Understand core concepts – risk-based regulation, accountability, transparency • Categorize AI use cases and risk levels
Major Regulatory Frameworks
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
Compliance and Internal Governance
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
Tools for Policy Implementation
Conduct impact assessments (AI, human rights, algorithmic, environmental) • Perform conformity assessments and post-market monitoring • Develop supplier and third-party due diligence
AI Policy Simulation Labs
Set up regulatory role-play (company, regulator, public) • Enforce the EU AI Act – mock review and assessment • Simulate U.S. risk management strategy
Innovation, Influence, and Next-Gen Governance
Explore sandbox models and experimental regulation • Engage in public participation and governance • Build regulatory foresight into AI strategy
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | EU AI Act |
| Covered Tool / Platform | U.S. Executive Orders |
| Covered Tool / Platform | OECD AI Principles |
| Covered Tool / Platform | UNESCO AI Ethics Recommendations |
Frequently Asked Questions
Scholar Feedback & Reviews
Based on 0 scholar submissions
Rating Breakdown
No verified reviews published yet. Be the first to share your academic experience.
Leave Scholar Feedback
Your rating will help prospective scholars. Ratings below 3 stars are routed privately to the faculty mentor for immediate response.
