
Lead AI Risk Manager
Lead AI risk management programs addressing bias, fairness, transparency, and regulatory compliance.
Course Description
This course develops expertise in managing AI-specific risks. Learn to identify, assess, and mitigate risks associated with AI systems including bias, fairness, transparency, robustness, and regulatory compliance.
Who Should Attend
- AI risk managers
- AI ethics officers
- Risk management professionals
- AI governance leads
Learning Objectives
- 1Identify and assess AI-specific risks
- 2Develop AI risk treatment strategies
- 3Implement AI risk monitoring and controls
- 4Lead AI risk governance programs
Prerequisites
- Understanding of AI technologies
- Risk management knowledge
Course Modules
Day 1: AI Risk Landscape and Regulatory Framework
AI risk categories and taxonomies; regulatory landscape (EU AI Act, NIST AI RMF); AI risk management frameworks; and AI system classification by risk level.
Day 2: AI Risk Assessment Methodology
Risk identification for AI systems; bias assessment techniques; fairness metrics; impact analysis; model risk assessment; and data quality risk evaluation.
Day 3: Risk Treatment, Controls, and Testing
AI risk treatment strategies; implementing AI safeguards; adversarial testing; red teaming for AI; model validation; and monitoring for drift and degradation.
Day 4: AI Ethics, Governance, and Compliance
Ethical AI frameworks; transparency and explainability requirements; AI governance structures; regulatory compliance management; stakeholder communication; and audit readiness.
Day 5: Certification Exam
Review of key concepts and the PECB Certified Lead AI Risk Manager certification examination.
Exam Details
Duration
3 hours
Format
Multiple choice (80 questions), open book
Passing Score
70%
Retake Policy
Free retake within 12 months after first failure
Available in:
Certification
PECB Certified Lead AI Risk Manager
Issued by PECB
Digital Badge & Verification

Verified via Credly
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