This advanced course provides a practical, end-to-end approach to governing, securing, and auditing AI systems in enterprise environments. Learners begin by examining adversarial threats to AI systems—including jailbreaks, prompt injection, data leakage, manipulation, and misinformation attacks—and practice structured red teaming using both manual and automated techniques. Participants learn how to analyze vulnerability severity and exploitability, prioritize remediation, and evaluate AI system readiness under adversarial conditions while communicating findings through clear, audit-ready documentation.

AI Risk and Compliance: Audit and Governance Foundations
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AI Risk and Compliance: Audit and Governance Foundations
This course is part of Managing AI Systems: Development, Deployment, and Governance Specialization

Instructor: Board Infinity
Included with
Recommended experience
What you'll learn
Execute adversarial red teaming scans using Giskard to identify and prioritize AI vulnerabilities
Classify AI systems under the EU AI Act and apply NIST AI RMF across the AI lifecycle
Generate SHAP/LIME explanations and create audit-ready transparency documentation
Implement guardrails, PII scrubbing with Presidio, and governance controls to mitigate Shadow AI
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April 2026
16 assignments
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There are 4 modules in this course
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Board Infinity

Board Infinity
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