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
This program helps stakeholders design ethics-by-design processes, build AI governance committees, conduct impact assessments, and align with regulatory frameworks such as the EU AI Act, OECD Principles, NIST AI RMF, and corporate ESG standards. Across 3 Weeks, you will work hands-on with EU AI Act, OECD Principles, and NIST AI RMF, then consolidate everything in a capstone project. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This program helps stakeholders design ethics-by-design processes, build AI governance committees, conduct impact assessments, and align with regulatory frameworks such as the EU AI Act, OECD Principles, NIST AI RMF, and corporate ESG standards.
📋 Course Objectives
1. Develop hands-on skill in EU AI Act.
2. Master the fundamentals of OECD Principles.
3. Get comfortable working with NIST AI RMF.
4. Apply AI Enablement methods to authentic research and industry problems.
5. 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
• Data and computational scientists moving into EU AI Act
🚀 Key Learning Outcomes
• Confidence to apply EU AI Act in real projects.
• Confidence to implement OECD Principles in real projects.
• Confidence to reason about NIST AI RMF in real projects.
• A demonstrable AI Enablement project for your research or industry portfolio.
• 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
Principles of Ethical AI
Explore the core values and global norms of Ethical AI • Identify common ethical challenges in AI systems • Discuss human rights, justice, and autonomy in AI contexts
From Ethics to Action
Translate ethical principles into organizational policies • Avoid ethics washing and empty frameworks • Apply ethics in product lifecycle: design, development, and deployment
Building Organizational Structures
Define roles and responsibilities for ethics leads, review boards, and committees • Create cross-functional ethics teams • Integrate ethics into product development and ML Ops
Tools and Frameworks for Responsible AI
Conduct impact assessments for algorithmic, human rights, and environmental aspects • Apply transparency and explainability in practice • Utilize auditing, monitoring, and documentation tools
Accountability and Escalation Paths
Manage incidents and red flags in AI systems • Establish whistleblower protections and ethical dissent channels • Report to leadership, boards, and the public
Culture, Strategy, and Long-Term Impact
Shape organizational culture around responsible innovation • Communicate ethical commitments to stakeholders • Develop metrics, KPIs, and incentives for ethical performance
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | OECD |
| Covered Tool / Platform | ISO 42001 |
| Covered Tool / Platform | NIST AI RMF |
| Covered Tool / Platform | Impact Assessments |
Frequently Asked Questions
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