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
Agile and Responsible AI Product Design is a cutting-edge program that blends agile product development strategies with ethical AI design principles. As AI becomes embedded in products and services across sectors, it is crucial not only to build fast—but also to build responsibly. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
Agile and Responsible AI Product Design is a cutting-edge program that blends agile product development strategies with ethical AI design principles. As AI becomes embedded in products and services across sectors, it is crucial not only to build fast—but also to build responsibly.
📋 Course Objectives
1. Translate AI Enablement theory into practical, reproducible analysis.
2. Assemble a documented case study that evidences your applied capability.
👥 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 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
Foundations of Agile Product Design for AI
Explore the overview of Agile in AI Product Development • Understand why AI requires a different Agile mindset • Compare Agile Frameworks adapted for AI: Scrum, Kanban, and CRISP-DM
Principles of Responsible AI
Define Fairness, Accountability, Transparency, and Ethics (FATE) • Analyze guidelines from OECD, IEEE, and the EU AI Act • Examine common failures in AI Ethics and their impact • Grasp the Product Manager’s role in ensuring Responsible AI
Agile Planning and Experimentation with AI
Implement iterative learning with AI: Data Loops and Feedback • Develop User Story Mapping for AI Features • Define Acceptance Criteria for Non-Deterministic Systems • Design ethical sprint cycles for AI product development
Human-Centered AI Product Design
Apply inclusive design principles in AI Products • Enhance explainability and user trust in AI interfaces • Construct Human-in-the-Loop Systems • Test AI Products effectively with real users
Governance and Responsible Delivery
Manage risk and implement robust model governance • Ensure data provenance, consent, and privacy compliance • Create essential documentation: Model Cards, Data Sheets, Fact Sheets • Integrate monitoring and retraining as agile extensions
Strategy, Roadmaps, and Capstone Project
Develop product roadmaps aligned with Responsible AI Principles • Communicate ethical impact effectively to stakeholders • Undertake a Capstone Project – Design a Responsible AI Feature • Participate in review, peer critique, and final presentation
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Agile frameworks (Scrum |
| Covered Tool / Platform | Kanban) |
| Covered Tool / Platform | CRISP-DM |
| Covered Tool / Platform | OECD AI Guidelines |
| Covered Tool / Platform | IEEE Ethically Aligned Design |
| Covered Tool / Platform | EU AI Act |
| Covered Tool / Platform | Model Cards |
| Covered Tool / Platform | Data Sheets |
| Covered Tool / Platform | Fact Sheets |
Frequently Asked Questions
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