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PMI CPMAI Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data for AI- Data identification and governance
  • 1. Data sourcing and selection
    • 2. Data compliance and ethics
      Topic 2: AI Model Development and Iteration- Model building and validation
      • 1. Machine learning / generative AI model development
        • 2. Iterative delivery approach
          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 Preparation for AI- Data cleaning and transformation
              • 1. Feature engineering and preparation
                • 2. Data quality assurance
                  Topic 5: AI System Testing and Evaluation- Model evaluation and monitoring
                  • 1. Performance evaluation and drift detection
                    • 2. Explainability and reliability assessment
                      Topic 6: AI Operationalization and Governance- Deployment and lifecycle management
                      • 1. Continuous improvement and monitoring
                        • 2. AI governance and responsible AI

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                          PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q204-Q209):

                          NEW QUESTION # 204
                          A project team is overseeing the data evaluation for an AI model predicting customer churn. They observed that the model's predictions are biased toward a particular class.
                          What is an effective technique to mitigate this bias?

                          Answer: B

                          Explanation:
                          Stratified sampling preserves appropriate class proportions when creating training or evaluation subsets. This helps ensure that each class is adequately represented, reducing class-related sampling bias and producing a more balanced assessment of the churn model.


                          NEW QUESTION # 205
                          An AI project team in the healthcare sector is tasked with developing a predictive model for patient readmissions. They need to gather required data from various sources, including electronic health records (EHR), patient surveys, and clinical notes. The team is evaluating which technique will help to ensure the data is comprehensive and reliable. What is an effective technique the project team should use?

                          Answer: A

                          Explanation:
                          Employing natural language processing helps extract relevant information from unstructured clinical notes, making the dataset more comprehensive and reliable for predicting patient readmissions. This ensures important patient context that is not stored in structured EHR fields or surveys can still be used effectively.


                          NEW QUESTION # 206
                          During CPMAI Phase II it's important to not only understand the sources of your data, but also what data is required for training as well as identifying the features that are required. When looking to gather data, what approach is best when determining how much data you need?

                          Answer: C

                          Explanation:
                          The "goldilocks" approach focuses on gathering an optimal amount of data - enough to train effective models without unnecessary excess - balancing quality and quantity for best results.


                          NEW QUESTION # 207
                          A team has started working on their first AI project and they are running this project like a traditional software development project. About two months into the project the team is hitting some major issues, and you're tasked with coming in to help manage this project. Immediately you realize that AI projects need to be treated like data centric projects.
                          What's the next best course of action?

                          Answer: A


                          NEW QUESTION # 208
                          You're in charge of marketing at your organization and you've been tasked with using AI to help create marketing images. What's a good solution for this need?

                          Answer: C

                          Explanation:
                          Generative AI is designed to create new content, such as marketing images, by learning patterns from existing data and generating novel outputs.


                          NEW QUESTION # 209
                          ......

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