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PMI CPMAI Exam Syllabus Topics:

SectionWeightObjectives
AI System Testing and Evaluation- Model evaluation and monitoring
  • 1. Performance evaluation and drift detection
    • 2. Explainability and reliability assessment
      Data for AI- Data identification and governance
      • 1. Data sourcing and selection
        • 2. Data compliance and ethics
          Data Preparation for AI- Data cleaning and transformation
          • 1. Feature engineering and preparation
            • 2. Data quality assurance
              Identify Business Needs and Solutions26%- Problem framing and business alignment
              • 1. Feasibility and ROI analysis
                • 2. Define AI business objectives
                  AI Model Development and Iteration- Model building and validation
                  • 1. Iterative delivery approach
                    • 2. Machine learning / generative AI model development
                      AI Operationalization and Governance- Deployment and lifecycle management
                      • 1. Continuous improvement and monitoring
                        • 2. AI governance and responsible AI

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                          PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q312-Q317):

                          NEW QUESTION # 312
                          Your organization wants to keep an eye on AI systems for Governance purposes. What are the most crucial things to consider? (Select all that apply.)

                          Answer: A,D,F,G


                          NEW QUESTION # 313
                          A healthcare organization plans to develop an AI-driven diagnostic tool. To define the required data, the project manager needs to ensure data consistency and accessibility. Which method should the project manager use?

                          Answer: A

                          Explanation:
                          Performing a data quality assessment with extraction, transformation, and loading processes helps ensure healthcare data is consistent, accessible, cleaned, transformed, and prepared in a usable format for the diagnostic AI tool.


                          NEW QUESTION # 314
                          Your organization wants to use Generative AI. What are examples of when Generative AI can and should be used? (Select all that apply.)

                          Answer: C,D,E,F


                          NEW QUESTION # 315
                          A manufacturing company is using an AI system for quality control. The project manager needs to ensure data privacy and compliance with industry standards. Which initial approach will effectively address these requirements?

                          Answer: C

                          Explanation:
                          Developing a comprehensive data governance plan is the most effective initial approach because it defines how data is collected, stored, accessed, protected, retained, and monitored in alignment with privacy obligations and industry standards.


                          NEW QUESTION # 316
                          An aerospace company is operationalizing an AI system to optimize flight routes. The system must be safe and comply with aviation regulations. The project team is evaluating methods to prevent potential safety risks.
                          Which method should the project manager use to prevent safety risk issues?

                          Answer: C

                          Explanation:
                          Extensive simulation testing exposes the AI system to a wide range of normal, abnormal, and edge-case flight conditions before operational use. This helps identify unsafe behaviors and failure modes early, allowing the team to address safety risks before they affect real-world flight operations.


                          NEW QUESTION # 317
                          ......

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