This course focuses on AI governance frameworks, risk management, regulatory requirements, ethical AI principles, and organizational AI oversight, aligning closely with the AIGP exam.
Overview
AIGP Certification Prep Training is an intensive three-day program designed to prepare professionals for the Artificial Intelligence Governance Professional (AIGP) certification exam. This course focuses on AI governance frameworks, risk management, regulatory requirements, ethical AI principles, and organizational AI oversight, aligning closely with the AIGP exam domains to help participants build exam readiness while gaining practical, real-world AI governance knowledge.
Learning Outcomes
• Understand AIGP certification concepts
• Learn AI governance fundamentals
• Understand responsible AI practices
• Gain knowledge of AI risk management
• Learn AI compliance and policy concepts
• Understand ethical AI frameworks
• Explore AI lifecycle governance
• Prepare for AIGP certification assessment
Duration & Delivery Mode
21 hours
Target Audience
• Governance, risk, and compliance professionals
• Legal, privacy, and policy professionals
• AI program managers and leaders
• Technology risk and audit professionals
• Candidates preparing for the AIGP certification exam
Pre-requisites
• Basic understanding of artificial intelligence concepts
• Familiarity with governance, risk, compliance, or policy functions
• Experience in technology, legal, compliance, or risk roles is beneficial
• Interest in AI governance and certification preparation
Skillset Achieved
• Understanding AI governance frameworks and principles
• Interpreting AI regulations and compliance requirements
• Applying AI risk management and oversight practices
• Preparing effectively for the AIGP certification exam
• Supporting responsible and compliant AI adoption
Course Outcome
By the end of this training, participants will be able to apply AI governance frameworks, manage AI-related risks, understand regulatory expectations, and confidently prepare for and attempt the AIGP certification exam while supporting responsible AI adoption in their organizations.
Course Outline
Foundations of AI Governance
• Purpose and scope of AI governance
• AI lifecycle and governance touchpoints
• Roles and responsibilities in AI governance
• Overview of AIGP exam structure and domains
AI Risk Management and Controls
• Identifying AI-specific risks
• Model, data, and operational risks
• Risk assessment and mitigation strategies
• Internal controls and accountability
AI Policies and Organizational Oversight
• Developing AI governance policies
• Establishing AI oversight committees
• Documentation and decision traceability
• Aligning governance with business strategy
Ethical and Responsible AI Principles
• Fairness, accountability, and transparency
• Bias, discrimination, and impact assessment
• Human oversight and explainability
• Embedding ethics into AI programs
AI Regulations and Legal Considerations
• Global AI regulatory landscape
• Data protection and privacy requirements
• Sector-specific AI compliance considerations
• Regulatory expectations and audits
AI Lifecycle Governance
• Governance during design and development
• Validation, testing, and deployment controls
• Monitoring, drift management, and retirement
• Continuous governance improvement
Operationalizing AI Governance
• Integrating governance into AI workflows
• Third-party and vendor AI risk management
• Incident response and escalation
• Measuring governance effectiveness
AIGP Exam Readiness and Practice
• Mapping course topics to AIGP exam objectives
• Sample questions and scenario analysis
• Exam strategies and time management
• Common pitfalls and best practices
Future of AI Governance
• Emerging governance standards and frameworks
• Preparing organizations for evolving AI laws
• Strategic role of AIGP professionals
• Long-term AI governance maturity
Assessment Topics
• AI governance fundamentals
• Responsible AI concepts
• AI risk management techniques
• AI compliance and policy frameworks
• Ethical AI considerations
• AI lifecycle governance
• Data privacy and protection basics
• AI accountability and transparency
• Governance use-case scenarios
• AIGP certification practice questions
Evaluation
• AI governance scenario analysis
• Risk and compliance assessment exercise
• AIGP-style practice questions
• Final knowledge evaluation quiz
Course Materials
Participants will receive course materials, slides, reference materials, exercises and access to resources for further learning.
Certification
None
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What Our Students Say
This course provided an excellent structure for understanding AI governance and preparing for the AIGP exam.
The mapping of governance topics to exam objectives was extremely helpful.
A well-organized program combining theory, practice, and certification readiness.
The regulatory and ethics modules were particularly strong.
An outstanding preparation course for professionals serious about AI governance.