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Cybersecurity Specialization: AI Risk Management Framework

SS Course: GK840108

Course Overview

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As artificial intelligence becomes increasingly embedded in critical systems, managing its risks is no longer optional it s essential. This two-day, hands-on course is designed to equip AI practitioners, cybersecurity professionals, risk managers, and compliance leaders with the tools and frameworks needed to navigate the complex landscape of AI risk. Participants will explore the structure and application of the NIST AI Risk Management Framework (AI RMF), compare it with global standards such as the EU AI Act and Saudi Arabia s NCA AI & Data Governance Framework, and learn how to apply these principles to real-world scenarios.

Through a blend of expert-led instruction, interactive activities, and case-based exercises, learners will gain practical experience in identifying, assessing, and mitigating AI risks such as bias, explainability, and data privacy. The course emphasizes ethical governance and regulatory compliance, guiding participants in designing unified risk strategies that align with international standards. Whether you're building AI systems or overseeing their deployment, this course offers a comprehensive foundation for responsible and secure AI implementation.

                                                                  

Scheduled Classes

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09/15/25 - GVT - Virtual Classroom - Virtual Instructor-Led
10/27/25 - GVT - Virtual Classroom - Virtual Instructor-Led
12/01/25 - GVT - Virtual Classroom - Virtual Instructor-Led
01/05/26 - GVT - Virtual Classroom - Virtual Instructor-Led
02/12/26 - GVT - Virtual Classroom - Virtual Instructor-Led
03/26/26 - GVT - Virtual Classroom - Virtual Instructor-Led
04/16/26 - GVT - Virtual Classroom - Virtual Instructor-Led

Outline

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  1. Introduction to AI Risk Management and Global Frameworks
    • Introduction to AI Risk Management
    • Overview of Key Global AI Frameworks
    • Mapping Global Frameworks to AI Risk Management Practices
    • AI Governance, Ethics, and Accountability
  2. Advanced AI Risk Management Strategies and International Compliance
    • Advanced Risk Management Strategies for AI Systems
    • Regional Variations
    • Case Studies: AI RMF and EU AI Act Implementation
    • Designing a Global AI Risk Management Strategy

    Prerequisites

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    • Participants should have a foundational understanding of AI systems and basic knowledge of risk management or cybersecurity principles.
    • Familiarity with regulatory concepts or frameworks (such as GDPR or NIST CSF) is helpful but not required.

      Who Should Attend

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      This course is designed for AI practitioners, risk managers, cybersecurity professionals, compliance officers, policymakers, and organizational leaders involved in the development, deployment, or oversight of AI systems.