Introduction to AI risk management Introduction to AI risk management concepts, objectives, and scope.
Introduction to AI risk managementIntroduction to AI risk management concepts, objectives, and scope.Organizational context, AI risk governance, and AI risk identificationUnderstanding organizational context, establishing AI risk governance structures, and identifying AI related risks.Analysis, evaluation, and treatment of AI risksMethods to analyze AI risks, evaluate their impact and likelihood, and define appropriate risk treatment measures.AI risk monitoring and reporting, training and awareness, and optimizing AI risk performanceMonitoring and reporting AI risks, building awareness and competence, and improving AI risk management performance.
Structured progression from fundamentals to application ensures retention.Each module reinforces previous learning while introducing new competencies.
“The curriculum aligns theory with applied practice.”
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Expert Trainer
Introduction to penetration testing, ethics, planning, and scoping Course objectives and structure Penetration testing principles Legal and ethical issues Fundamental principles of
Foundations of AI and Data Analysis Training course objectives and structure Fundamental concepts and principles of artificial intelligence Data analysis and visualization Machine
Introduction to the CMMC ecosystem and the CMMC model Overview of the CMMC ecosystem Structure and objectives of the CMMC model CMMC practices, assessment process, and code of prof
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