What topics are covered across the four course days?
Day 1 covers AI risk fundamentals; Day 2 covers context, governance, and risk identification; Day 3 covers analysis, evaluation, and treatment; Day 4 covers monitoring, reporting, awareness, and continual improvement.
Day 1 introduces AI risk management concepts and why AI creates distinctive risk categories beyond traditional risk programs.
Day 2 focuses on organizational context, AI risk governance, and risk identification—covering bias, security vulnerabilities, transparency limits, ethical concerns, and compliance exposure.
Day 3 covers analysis, evaluation, and treatment: prioritization, risk acceptance criteria, mitigation planning, and incident response measures.
Day 4 addresses monitoring and reporting, training and awareness, and optimizing AI risk performance through organizational learning and continual improvement.
Related Information
- Day 1: AI risk management foundations.
- Day 2: context, governance, identification.
- Day 3: analysis, evaluation, treatment.
- Day 4: monitoring, reporting, awareness, improvement.
- Course uses exercises and quizzes aligned to exam style.
Expert Insight
Track outputs as you learn: a risk register, control plan, monitoring metrics, and escalation paths. Those artifacts map directly to exam domains and real work.
Topics
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