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PMI CPMAI Exam Syllabus Topics:

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

                          >> New CPMAI Exam Topics <<

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                          PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q264-Q269):

                          NEW QUESTION # 264
                          An organization is planning to use AI for real-time auctions and bidding. Which AI capability should be implemented to meet the organization's objectives?

                          Answer: D

                          Explanation:
                          Autonomous systems can independently make decisions and take actions in dynamic, rapidly changing environments. For real-time auctions and bidding, they can continuously evaluate conditions, adjust bids, and execute bidding decisions without requiring constant human intervention.


                          NEW QUESTION # 265
                          A government agency is operationalizing an AI system to optimize urban traffic flow that changes unexpectedly. The project manager needs to gather the required data from traffic cameras, sensors, and historical traffic patterns. What is an effective technique to meet the project manager's goals?

                          Answer: B

                          Explanation:
                          PMI's CPMAI-aligned guidance emphasizes that AI initiatives must be managed as continuous lifecycles and that teams must address the gap between models and real-world implementation, including challenges such as changing conditions that can drive performance degradation (e.g., drift). In a traffic optimization use case where conditions change unexpectedly, the governing need is not merely to have more data, but to ensure the AI solution is operating on current, synchronized inputs across multiple data sources (cameras, sensors, historical patterns) so that recommendations reflect the present state of the system. Real-time synchronization directly supports this by aligning timestamps, ensuring consistent ingestion across feeds, and enabling timely analysis for decision- making when traffic conditions shift quickly. This approach best matches the operational objective of optimizing a dynamic environment because it reduces latency and inconsistency between streams, which otherwise can lead to outdated or conflicting interpretations.


                          NEW QUESTION # 266
                          An IT services company is integrating an AI solution to automate its customer service functions.
                          The integration team is facing resistance from the customer's employees.
                          Which action should the project manager perform to manage this risk?

                          Answer: A


                          NEW QUESTION # 267
                          A project manager meets with a customer for initial discussions about an upcoming project. At the end of the meeting, the customer asks the project manager for a rough estimate of the project duration. Based on her experience with three similar projects, the project manager provides an estimate of 8-10 months. What's wrong with this timeframe?

                          Answer: C

                          Explanation:
                          The estimate likely overlooks the significant time required for data preparation, which is a critical and often time-consuming phase in AI projects.


                          NEW QUESTION # 268
                          Your team is starting a new facial recognition project and you want to ensure that the project is being done with Trustworthy AI in mind.
                          At what phase of CPMAI would Trustworthy AI be considered?

                          Answer: E


                          NEW QUESTION # 269
                          ......

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