Programme Parameters
Advanced Postgrad
1 Day (1.5 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
Advanced AI and Ethics: Governance and Regulation is a deeper, self-paced treatment for those who already grasp the basics and need to operationalise responsible AI at scale. You work through mature governance and risk-management frameworks, the detail of major regulatory regimes (the EU AI Act, NIST AI RMF and sector rules), and how to embed accountability across an AI lifecycle — from impact assessment to audit and monitoring. The emphasis is implementation and organisational maturity. You finish able to design and run an advanced AI-governance programme. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This advanced self-paced course covers AI governance and regulation in depth — mature risk frameworks, global regulatory regimes and operationalising accountable AI at scale.
📋 Course Objectives
1. Apply mature AI governance and risk frameworks.
2. Work in depth with the EU AI Act and NIST AI RMF.
3. Embed accountability across the AI lifecycle.
4. Run impact assessments and audits.
5. Build organisational AI-governance maturity.
👥 Who Should Enroll?
• AI governance and risk leads
• Compliance and legal professionals
• Senior product and policy staff
• Students of advanced AI policy
🚀 Key Learning Outcomes
• Advanced AI-governance capability.
• An implementation-ready framework.
• An organisational-maturity perspective.
• 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
AI Governance Frameworks and International Regulations
Comprehensive overview of global AI regulatory standards, including the EU AI Act and U.S. AI Guidelines. • Sector-specific regulations in critical industries such as healthcare, finance, and autonomous vehicles. • Case studies like the impact of GDPR on AI and China’s Social Credit System.
Advanced Ethical Decision-Making in AI
Delve into complex ethical dilemmas faced in AI development, such as bias, fairness, and accountability. • Learn advanced ethical frameworks and how to apply them to AI systems. • Case studies on AI failures, including Amazon’s biased recruitment algorithm and the ethical issues in predictive policing.
Emerging AI Technologies and Ethical Considerations
Explore the ethical challenges of cutting-edge AI technologies like quantum AI, AI in genomics, and autonomous weapons. • Examine the ethical implications of AI surveillance systems and autonomous decision-making. • Understand the environmental impacts of AI technologies and how to create sustainable AI systems.
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | TensorFlow |
| Covered Tool / Platform | PyTorch |
| Covered Tool / Platform | Keras |
| Covered Tool / Platform | Scikit-learn |
| Covered Tool / Platform | Jupyter Notebook |
| Covered Tool / Platform | Google Colab |
| Covered Tool / Platform | Hugging Face |
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