Assess AI systems for fairness, privacy, documentation and governance, with examples from international guidance and Indian privacy requirements. 1. Who can join Suitable for: AI product owners, compliance teams, IT managers and technical leads Mandatory prerequisites: Basic familiarity with AI systems; no programming mandatory for policy track 2. Duration 24 live hours • Approximately 4 weeks at 6 hours per week; actual timetable to be confirmed. 3. Mode Classroom - Thaiyur / Kelambakkam, OMR Chennai (subject to schedule) Live Online (subject to schedule)
4. Syllabus — five modules
Module 1: AI Governance Frameworks & Regulatory Landscape (EU AI Act, NIST AI RMF) Learning outcome: Recognize major AI governance frameworks and regulatory themes. Module 2: Detecting & Mitigating Algorithmic Bias in Dataset Features Learning outcome: Spot likely bias sources and propose mitigation tests. Module 3: Data Privacy Standards: Anonymization, Differential Privacy & GDPR/HIPAA Learning outcome: Document sensitive-data handling and privacy controls. Module 4: Explainable AI (XAI) Systems & Model Audit Logging Learning outcome: Define explainability, logging and audit evidence requirements. Module 5: Designing Corporate AI Usage Policies & Ethics Review Boards Learning outcome: Draft a sample organizational AI-use policy and review workflow. 5. Practical project Source capstone title: Conduct an End-to-End AI Safety & Compliance Audit on a Deployed Model Student deliverable: A structured AI risk review covering use-case inventory, data handling, bias checks, human oversight and a remediation checklist.
6. What is included Live trainer-led sessions Practical assignments Sample code or templates, as applicable Project feedback Learning assessment Perizona course-completion certificate subject to assessment 7. Upcoming batch Start date: To be announced. Students can register interest; dates are shared only after confirmation.
