CPMAI practice questions 101–110

1. Question 101 · 192 in bank

   A project manager overseeing an AI project is concerned about potential data privacy violations. Before progressing further with the project, what should the project manager do to address this concern?

   • AEstablish a cross-functional team to handle data governance.
   • BDevelop a comprehensive data risk management framework.
   • CImplement real-time monitoring tools for data access control.
   • DConduct a thorough compliance audit against data regulations.

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   Answer: D

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2. Question 102 · 192 in bank

   A healthcare provider had physicians review a potential diagnostic AI application. During their final review, the project team along with the physicians, discovered that the AI model exhibits a higher than acceptable false-positive rate. Before making the go/no-go AI decision, which next step should be performed by the team?

   • AReevaluate the business objectives and outcomes.
   • BFocus on the model’s ethical implications.
   • CAdjust the hyperparameters for better generalization.
   • DIncrease the training data volume.

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   Answer: A

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3. Question 103 · 192 in bank

   A company’s leadership team has requested insights into the AI model’s ability to support decision-making processes without requiring them to understand complex technical details. Which step should the project manager take?

   • ADiscuss how ensemble methods improve the model's robustness.
   • BExplain the role of neural network architectures in prediction accuracy.
   • CDemonstrate how the model's output can be integrated and used in end-user systems.
   • DDescribe the model’s backpropagation and gradient descent optimization.

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   Answer: C

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4. Question 104 · 192 in bank

   In a clustering analysis for data use, the project team finds that the clusters are not meaningful and do not provide actionable insights. Which activity should the project manager do with the project team?

   • AEstablish data governance protocols.
   • BConduct an algorithm analysis on the data sources.
   • CAssess the trade-offs of the various algorithms.
   • DIdentify the data gaps and address deficiencies.

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   Answer: D

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5. Question 105 · 192 in bank

   A project manager is evaluating whether an AI model is ready for operationalization. The project team has ensured the model meets accuracy and performance requirements and has conducted extensive testing. However, uncertainty about the model’s operationalization in different environments and its compliance with regulatory standards still exists. What should the team do next?

   • AImplement additional noncognitive solutions.
   • BConsider retraining the model for better performance.
   • CEvaluate the model’s adaptability to diverse conditions.
   • DReassess the project’s data preparation phase.

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   Answer: C

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6. Question 106 · 192 in bank

   A healthcare organization is developing an Al model to predict patient outcomes. The project manager needs to address issues of missing or incorrect data before training the model. What is an effective method to help ensure data quality?

   • APerforming systematic data validation
   • BEnhancing with data augmentation techniques
   • CImplementing an AI data needs assessment
   • DApplying predictive data algorithms

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   Answer: A

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7. Question 107 · 192 in bank

   A transportation company is preparing data for an AI model to optimize fleet management. The project team is working with large amounts of structured and unstructured data. If the project manager avoids addressing the variety of data during preparation, what will be the result?

   • ADecreased data processing speed
   • BIncreased data consistency
   • CReduced model performance
   • DImproved model accuracy

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   Answer: C

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8. Question 108 · 192 in bank

   A healthcare project manager is evaluating whether to implement an AI-powered diagnostic tool. The initial cost is US$500,000 with an expected return on investment (ROI) of 15% within the first year. The project needs to satisfy multiple stakeholders including hospital administrators and medical staff. Which method will maximize a positive ROI for the AI implementation?

   • AMonitoring AI model performance against key performance indicators.
   • BEnsuring all AI and non-AI components are integrated seamlessly.
   • CAcquiring alternatives to the AI solution as a contingency plan.
   • DSeeking verbal commitments from interested parties at each project phase.

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   Answer: A

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9. Question 109 · 192 in bank

   A team is evaluating different AI models for their project. They are considering error rates and overall performance. If the team had selected a model based solely on the error rate, what would be the outcome?

   • AA balanced performance across all metrics
   • BAn increase in stakeholder satisfaction based on performance
   • CA better performance across the chosen domains
   • DA potential to overlook other critical performance metrics

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   Answer: D

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10. Question 110 · 192 in bank

    A financial services firm is building an AI model to detect fraudulent transactions. Identifying and validating data sources is critical to the model’s success. What is an effective method that helps to ensure data accuracy?

    • AUtilizing data lineage tools to track data origin and transformations
    • BEmploying a federated database system for decentralized data access
    • CSetting up a batch processing system for data cleansing
    • DImplementing a blockchain-based ledger for transaction data

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    Answer: A

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CPMAI practice, question 101. 192 questions available.