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PMI CPMAI Exam Syllabus Topics:

SectionWeightObjectives
AI Model Development and Iteration- Model building and validation
  • 1. Iterative delivery approach
    • 2. Machine learning / generative AI model development
      AI System Testing and Evaluation- Model evaluation and monitoring
      • 1. Explainability and reliability assessment
        • 2. Performance evaluation and drift detection
          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
                  Data for AI- Data identification and governance
                  • 1. Data compliance and ethics
                    • 2. Data sourcing and selection
                      Data Preparation for AI- Data cleaning and transformation
                      • 1. Data quality assurance
                        • 2. Feature engineering and preparation

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                          Web-based Cognitive Project Management in AI (PMI-CPMAI) (CPMAI) practice exam is a convenient format to evaluate and improve preparation for the exam. It is a CPMAI browser-based application, which means you can access it from any operating system with an internet connection and a web browser. Unlike the desktop-based exam simulation software, the Cognitive Project Management in AI (PMI-CPMAI) (CPMAI) browser-based practice test requires no plugins and software installation. It makes the PMI CPMAI online practice exam a perfect tool for those who do not want to go through complicated software installation on their device.

                          PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q49-Q54):

                          NEW QUESTION # 49
                          An AI project team has completed an AI go/no-go assessment. They have discovered several technology and data factors to be insufficient. Which action should occur?

                          Answer: B

                          Explanation:
                          When a go/no-go assessment shows insufficient technology and data factors, the team should not proceed until key readiness concerns are addressed. Verifying data quality and stakeholder alignment helps confirm whether the project can meet business goals, technical needs, and implementation expectations before development continues.


                          NEW QUESTION # 50
                          You're working with a small inexperienced team on a new ML project. Choosing the best algorithm with the best settings given the training and test data is proving to be very hard for them. You lack the critical data science resources available on your team, and can't wait weeks until a data science resource becomes available to join your team.
                          What's your best course of action?

                          Answer: C


                          NEW QUESTION # 51
                          A project manager is overseeing the transition of a company's legacy system to a new AI-driven solution. The team has identified multiple cognitive patterns required for different aspects of the system. However, the project manager is concerned about overcomplicating the transition. When activity should be performed first?

                          Answer: D

                          Explanation:
                          Identifying parts of the project that do not require intelligent systems should be done first because it separates noncognitive automation needs from true AI cognitive patterns. This reduces unnecessary complexity and helps the team apply AI only where learning, reasoning, prediction, or decision support is actually required.


                          NEW QUESTION # 52
                          You are leading a project to develop a new predictive maintenance solution. Together with your project team you determine your data needs, see if you have access to the data, and then begin working on the project. Which phase best describes the work you are performing?

                          Answer: E

                          Explanation:
                          Phase II of CPMAI focuses on understanding and preparing data needs, including data acquisition and assessment before model development begins.


                          NEW QUESTION # 53
                          You just joined a new company and they want to start their first AI project. Senior management thinks the best approach is to just buy AI from a vendor. You know that AI is something you do, not something you buy.
                          What is your next best course of action to address this?

                          Answer: A


                          NEW QUESTION # 54
                          ......

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