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PMI CPMAI Exam Syllabus Topics:

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

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                          Latest CPMAI Test Simulator - Your Sharpest Sword to Pass Cognitive Project Management in AI (PMI-CPMAI)

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                          PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q106-Q111):

                          NEW QUESTION # 106
                          A hospital wants to develop a medical records system with the primary goal of minimizing or eliminating paper records. They have identified where the cognitive AI solution will be applied. In addition, business objectives have been quantified and key performance indicators (KPIs) have been determined.
                          What else needs to be done to progress to the next Cognitive Project Management for AI (CPMAI) phase?

                          Answer: D


                          NEW QUESTION # 107
                          You need to hire a data scientist to join your team. What skill sets should you be looking for when hiring and interviewing this person? (Select all that apply.)

                          Answer: A,B,D,F


                          NEW QUESTION # 108
                          A project team is preparing to move to the next phase of their AI project. The team needs to ensure that all transparency and explainability requirements are met. Which activity should the project team perform?

                          Answer: D

                          Explanation:
                          Documenting the decision-making process of the AI model directly supports transparency and explainability by showing how inputs are used, how outputs are generated, and how decisions can be reviewed or justified before moving to the next project phase.


                          NEW QUESTION # 109
                          A manufacturing company is operationalizing an AI-driven quality control system. The project manager needs to ensure data privacy and regulatory compliance due to the critical nature in protecting sensitive operational data. What is an effective technique that addresses these requirements?

                          Answer: D

                          Explanation:
                          Applying data anonymization protects sensitive operational data by removing or masking identifying information before it is used in the AI quality control system. This supports data privacy and helps meet regulatory compliance requirements while still allowing the dataset to be analyzed.


                          NEW QUESTION # 110
                          A team is retraining a model and creating a new version of that model. What's the most important thing for the team to have in place before doing this?

                          Answer: B

                          Explanation:
                          Model governance ensures proper version control, documentation, and compliance, which are critical before retraining and deploying new model versions.


                          NEW QUESTION # 111
                          ......

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