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PMI CPMAI Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Operationalization and Governance- Deployment and lifecycle management
  • 1. AI governance and responsible AI
    • 2. Continuous improvement and monitoring
      Topic 2: Data Preparation for AI- Data cleaning and transformation
      • 1. Data quality assurance
        • 2. Feature engineering and preparation
          Topic 3: Data for AI- Data identification and governance
          • 1. Data compliance and ethics
            • 2. Data sourcing and selection
              Topic 4: Identify Business Needs and Solutions26%- Problem framing and business alignment
              • 1. Define AI business objectives
                • 2. Feasibility and ROI analysis
                  Topic 5: AI System Testing and Evaluation- Model evaluation and monitoring
                  • 1. Explainability and reliability assessment
                    • 2. Performance evaluation and drift detection
                      Topic 6: AI Model Development and Iteration- Model building and validation
                      • 1. Iterative delivery approach
                        • 2. Machine learning / generative AI model development

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                          PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q42-Q47):

                          NEW QUESTION # 42
                          In the finance sector, a company is implementing an AI system for credit risk assessment. The project manager needs to identify the data subject matter experts (SMEs) who can help to ensure the accuracy and reliability of the model. What is an effective method to achieve this objective?

                          Answer: D

                          Explanation:
                          Internal data analysts and financial experts are best positioned to validate the relevance, quality, and interpretation of credit risk data because they understand both the technical data characteristics and the financial risk context needed for a reliable model.


                          NEW QUESTION # 43
                          A healthcare project manager is working on implementing an AI-driven diagnostic tool. The project requires identifying key resources, including data scientists, server infrastructure, and external AI consultants. The project manager needs to ensure the allocated resources are optimized for the project's success. Which method will help to ensure the optimal allocation of resources?

                          Answer: D

                          Explanation:
                          Applying the theory of constraints helps identify the most limiting resource or bottleneck, such as scarce data science capacity, server limitations, or consultant availability. Addressing that constraint first improves overall resource allocation and supports successful AI diagnostic tool implementation.


                          NEW QUESTION # 44
                          An organization needs a document classification capability. A commercial service already provides this function at acceptable accuracy, while an internal build would take an estimated nine months.
                          What should the project manager evaluate first?

                          Answer: B

                          Explanation:
                          Build decisions are justified when the capability provides differentiation that a commodity service cannot deliver. If the function is not a differentiator, buying conserves resources for work that creates distinct organizational value.


                          NEW QUESTION # 45
                          A project involves integrating AI systems across multiple departments, each with different access levels. This complex Al project has presented the project manager with significant issues related to data misuse. The project team has been focused on their ethics guidelines but continues to experience data misuse. The project involves different regional data protection regulations which further increases the complexity. What issue will cause these challenges to occur?

                          Answer: D

                          Explanation:
                          A detailed governance strategy is needed to define how data is accessed, used, shared, monitored, and controlled across departments and regions. Ethics guidelines alone are not enough when the project involves multiple access levels, potential misuse, and varying data protection regulations.


                          NEW QUESTION # 46
                          A supervised learning project requires 50,000 labeled images. The subject matter is highly specialized, and the organization has three qualified domain experts available part time.
                          What is the most significant project risk the manager should plan for?

                          Answer: A

                          Explanation:
                          Labeling is frequently the largest bottleneck in supervised learning projects, especially when it requires scarce domain expertise. The project manager must plan labeling capacity, cost, and duration explicitly rather than treating it as a minor preparation task.


                          NEW QUESTION # 47
                          ......

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