CPMAI practice questions 171–180

1. Question 171 · 192 in bank

   An AI project team is assessing the scalability of a healthcare solution. Which factor should the project manager consider to help ensure the solution is scalable?

   • ACompliance with data regulations
   • BHuman oversight requirements
   • CAbility to handle increased loads
   • DIntegration with the existing infrastructure

   Show answer

   Answer: C

   Next question

2. Question 172 · 192 in bank

   A consulting firm is preparing data for an AI-driven customer segmentation model. They need to verify data quality before data preparation. What should the project manager do first?

   • AImplement data enhancement.
   • BConduct data cleaning.
   • CAssess data completeness.
   • DApply data labeling techniques.

   Show answer

   Answer: C

   Next question

3. Question 173 · 192 in bank

   A telecommunications company is implementing an AI-driven customer support system. The project manager is responsible for overseeing the data evaluation. They need to ensure that the AI system provides accurate and helpful responses to customer queries. What is an effective method that helps to ensure these objectives are achieved?

   • AImplementing a static rule-based system alongside the AI system to handle complex customer questions
   • BRegularly updating the AI system’s knowledge base with the latest information and feedback from customer interactions
   • CRelying on periodic training sessions for customer support staff to improve their understanding of the AI system
   • DConducting quarterly performance reviews using customer satisfaction surveys

   Show answer

   Answer: B

   Next question

4. Question 174 · 192 in bank

   An AI project team is in the process of designing a security plan. The team needs to consider various aspects such as transparency, explainability, and compliance with data regulations. Which action should the project manager take?

   • AEnsure the AI system’s decisions are transparent and explainable.
   • BRely solely on encryption without considering other security aspects.
   • CFocus only on technical security measures, ignoring transparency.
   • DAssume compliance without reviewing current regulations.

   Show answer

   Answer: A

   Next question

5. Question 175 · 192 in bank

   A project manager at a consulting firm is tasked with facilitating the creation of an AI-driven predictive maintenance system for a manufacturing client. Identifying data sources and locations is crucial for the project's success. Which method will help to ensure the project manager meets the objectives?

   • AOperationalizing a data lake for centralized storage
   • BUsing Internet of Things (IoT) sensors for real-time data collection
   • CEstablishing a comprehensive data governance framework
   • DCreating a detailed data flow diagram

   Show answer

   Answer: D

   Next question

6. Question 176 · 192 in bank

   A project team is tasked with ensuring all AI-related decisions and actions are documented comprehensively for future auditing purposes. They need to track the reasons for specific AI choices, their impacts, and any issues encountered during the implementation. What is represented in this situation?

   • AStrategic alignment
   • BOperational efficiency
   • CCompliance management
   • DTransparency

   Show answer

   Answer: D

   Next question

7. Question 177 · 192 in bank

   A manufacturing company is operationalizing an AI-driven quality control system. The project manager needs to ensure data privacy and regulatory compliance due to the critical nature in protecting sensitive operational data. What is an effective technique that addresses these requirements?

   • AImplementing a zero-trust architecture for network security
   • BUtilizing a secure multiparty computation framework
   • CApplying data anonymization to the dataset
   • DUsing a hybrid encryption scheme for storage

   Show answer

   Answer: C

   Next question

8. Question 178 · 192 in bank

   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?

   • AThe project can face unexpected scalability challenges.
   • BThe custom project development time can increase due to adjustments.
   • CThe team can see a reduction in the overall project timeline.
   • DThe team can encounter compatibility issues with existing systems.

   Show answer

   Answer: C

   Next question

9. Question 179 · 192 in bank

   An AI project team with a manufacturing company needs to ensure data integrity before moving to model development. They discovered some data inconsistencies due to manual entry errors. What is an effective method that helps to ensure data integrity?

   • AUsing machine learning algorithms to detect and correct errors
   • BAutomating data entry processes
   • CConducting regular audits of manually entered data
   • DImplementing real-time data validation rules

   Show answer

   Answer: D

   Next question

10. Question 180 · 192 in bank

    In the early stages of an AI project, the team needs to determine the types of environments and devices where the AI solution will be used. This information is crucial to ensure a successful implementation. Which action should the project manager implement first?

    • AConduct comprehensive user experience research.
    • BPerform a technical requirements audit.
    • CHold workshops with end users to gather feedback.
    • DDraft a detailed usage scenario analysis.

    Show answer

    Answer: D

    Next question

Keyboard:J Kmove between questionsA–Dselect an answerRshow or hide the answer← →change page

CPMAI practice, question 171. 192 questions available.