AI Governance, Model Risk & Responsible AI
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Curated Certification CGR08
Govern AI systems across use-case intake, accountability, model and agent risk, testing, transparency, privacy, safety, human oversight, monitoring and lifecycle decisions.
Benchmark: Curated source set: NIST + Microsoft Learn + Google Cloud Skills Boost -- Credential note: this is a Zuyini mastery certificate built from the cited public courses. It is not issued, sponsored or endorsed by the source institutions, providers or companies.
Core Course Stack
1. AI Risk Management Framework
2. NIST AI Resource Center / AI RMF Playbook
3. Design Responsible AI Security, Governance, Risk & Compliance
4. Govern AI-Ready Infrastructure
5. Scale Responsible AI Governance for Multi-Agent Systems
6. Secure & Govern Microsoft 365 Copilot with Purview
7. Introduction to Security in the World of AI
8. NIST Privacy Framework
Hands-On Mastery Capstone
Establish an AI governance process for a real or simulated AI/agent system. Classify use-case risk, assign accountability, define evaluation and human-oversight controls, assess privacy/safety risks and set deployment/monitoring gates.
Proof Rubric
- AI inventory
- risk tiering
- RACI
- model/agent risk assessment
- eval plan/results
- human oversight design
- transparency artifact
- monitoring/incident triggers
- launch decision