📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of Agile and Responsible AI Product Design, from foundations to a certified capstone project.
Outline
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
Outline
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
Outline
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
Outline
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
Outline
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
Outline
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
Earn government-registered certification in Agile and Responsible AI Product Design
e-Certificate and e-Marksheet issued on successful completion.
