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PMI CPMAI Exam Syllabus Topics:

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

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                          PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q88-Q93):

                          NEW QUESTION # 88
                          A project team is tasked with developing an AI system to optimize workflow efficiency by automating both cognitive and noncognitive tasks. The AI system will handle various tasks including data analysis and decision-making to routine administrative functions. The AI system needs to be integrated with the existing enterprise software and meet international regulations.
                          The team needs to manage data from multiple sources with different formats and standards. The AI system needs to evolve as business processes and technologies change. How would the results for the system be different if cognitive and noncognitive tasks are not separated?

                          Answer: C

                          Explanation:
                          When cognitive and noncognitive tasks are not separated, the solution may apply advanced AI methods to simple rule-based or repetitive work. This creates unnecessary complexity, higher cost, and inefficient use of AI capabilities that should be reserved for tasks requiring reasoning, learning, prediction, or decision support.


                          NEW QUESTION # 89
                          In the case that an algorithm you want to use isn't algorithmically explainable, AI systems should try to do the following:

                          Answer: A


                          NEW QUESTION # 90
                          A company needs to launch an AI application quickly to be the first to the market. The project team has decided to use pretrained models for their current AI project iteration. What is a key result of leveraging pretrained models?

                          Answer: B

                          Explanation:
                          Leveraging pretrained models can reduce the overall project timeline because the team starts from an existing model that has already learned general patterns. This can shorten development, training, and experimentation time for the current AI project iteration.


                          NEW QUESTION # 91
                          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 # 92
                          A financial services firm is integrating AI to enhance fraud detection. To oversee data evaluation, the project manager needs to ensure the integrity and accuracy of input data, including transaction histories and customer profiles. Which method provides the results that address the requirements?

                          Answer: D

                          Explanation:
                          Using a fact checklist provides a systematic way to verify the integrity, accuracy, completeness, and reliability of transaction histories and customer profiles before they are used by the fraud detection model.


                          NEW QUESTION # 93
                          ......

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