PMI Certified Professional in Managing AI (PMI-CPMAI™) Exam Preparation Training Course

Module 1: Introduction to PMI Certified Professional in Managing AI (PMI-CPMAI)

• Overview of the PMI-CPMAI™ certification
• Role of AI-focused project management
• Examination structure and preparation approach
• Core concepts tested in the PMI-CPMAI™ examination
• AI project manager responsibilities
• AI project lifecycle fundamentals

Module 2: Fundamentals of Artificial Intelligence

• Definition and characteristics of artificial intelligence
• AI technologies and applications
• Generative AI and predictive AI
• AI systems and business use cases
• AI project characteristics
• Opportunities and limitations of AI technologies

Module 3: AI Project Management Fundamentals

• Principles of AI project management
• AI project initiation and planning
• Defining AI project objectives and outcomes
• AI project scope and requirements
• AI project lifecycle management
• Managing uncertainty and evolving requirements

Module 4: Machine Learning for Project Professionals

• Fundamentals of machine learning
• Supervised and unsupervised learning
• Training, validation, and testing concepts
• Data requirements for machine learning
• Model performance and evaluation
• Machine learning project risks and dependencies

Module 5: AI Project Planning and Requirements

• Identifying AI project stakeholders
• Defining business and technical requirements
• Data and model considerations
• AI project deliverables and acceptance criteria
• Planning AI resources and capabilities
• Developing AI project roadmaps

Module 6: Managing AI Data and Model Considerations

• Data quality and data governance
• Data preparation and management
• Data privacy and security considerations
• Model development lifecycle
• Model evaluation and performance monitoring
• Managing data and model-related project risks

Module 7: Responsible AI and Governance

• Principles of responsible AI
• AI ethics and accountability
• Transparency and explainability
• Bias and fairness considerations
• Privacy and security
• AI governance frameworks
• Managing responsible AI throughout the project lifecycle

Module 8: AI Project Risk and Stakeholder Management

• Identifying AI-specific risks
• Technical, operational, and organisational risks
• Managing AI uncertainty
• Stakeholder identification and engagement
• Communicating AI project risks and outcomes
• Cross-functional collaboration between technical and business teams

Module 9: Executing, Monitoring, and Controlling AI Projects

• AI project execution practices
• Monitoring AI project performance
• Managing changes and emerging requirements
• Measuring AI project outcomes
• Managing project issues and corrective actions
• Tracking technical and business performance indicators

Module 10: PMI-CPMAI™ Exam Preparation

• Review of PMI-CPMAI examination domains
• Key terminology and concepts
• Scenario-based examination questions
• Practice questions and mock assessments
• Examination strategies and time management
• Identifying common examination challenges
• Final PMI certification preparation and revision