CPMAI–100% Free Exam Questions Answers | Trustable Test Cognitive Project Management in AI (PMI-CPMAI) Quiz

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PMI CPMAI Exam Syllabus Topics:

Section	Weight	Objectives
Support Responsible and Trustworthy AI Efforts	15%	- Ensure fairness, transparency, accountability - Establish ethical and governance frameworks - Manage bias, risk, compliance, and societal impact
Manage AI Model Development and Evaluation	16%	- Oversee model design, training, and validation - Address model drift, explainability, and limitations - Monitor performance, accuracy, and reliability
Identify Business Needs and Solutions	26%	- Define requirements, scope, and success criteria - Evaluate feasibility and value of AI solutions - Align AI initiatives with organizational strategy
Operationalize AI Solution	17%	- Deploy AI systems into production - Manage change, adoption, and governance post-launch - Establish monitoring, maintenance, and improvement processes
Identify Data Needs	26%	- Ensure data quality, privacy, security, and compliance - Plan data collection, storage, and infrastructure - Define data requirements and sources

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q213-Q218):

NEW QUESTION # 213
A project manager is overseeing the development of an AI system and is concerned about maintaining user privacy. The project involves collecting sensitive user data with potential legal and compliance issues to consider.
What should the project manager prioritize to help ensure the AI system adheres to privacy requirements?

A. Implementing a minimalistic data collection policy
B. Ensuring regular impact assessments are conducted to meet privacy laws
C. Establishing robust data encryption protocol for privacy
D. Developing a comprehensive data anonymization strategy

Answer: B

Explanation:
Regular privacy impact assessments help identify how sensitive data is collected, processed, stored, and used, while evaluating associated privacy risks against applicable legal and regulatory requirements. This enables the project team to maintain ongoing compliance throughout the AI system's lifecycle.

NEW QUESTION # 214
You want to create a model to figure out if a customer would be likely to repurchase a certain item. The project owner doesn't want you to create anything too complicated, and you have a limited data set to work with.
Which algorithm is the best choice given these constraints?

A. Naive Bayes
B. Neural Networks
C. Ensemble models
D. Generative AI

Answer: A

NEW QUESTION # 215
During the planning phase, a project manager identifies multiple patterns for their AI project.
Which two actions should the project manager do? (Choose two.)

A. Focus on noncognitive parts before addressing cognitive patterns.
B. Split the project into iterations for different patterns.
C. Select patterns based on stakeholder preference.
D. Combine all patterns into a single comprehensive iteration.
E. Proceed with the most complex pattern to challenge the team.

Answer: A,B

Explanation:
Splitting the project into iterations allows each AI pattern to be planned, tested, and refined separately, reducing complexity and improving control. Addressing noncognitive parts first can establish stable process automation and integration foundations before introducing more complex cognitive AI capabilities.

NEW QUESTION # 216
Your team is trying to determine which pattern best fits their AI problem. To do this the project team is running through the seven patterns of AI to figure out what pattern best applies to their problem. Which of the following is the best approach?

A. When in doubt, go with the patterns and anomalies pattern as all AI projects are about pattern matching.
B. When in doubt, don't apply any pattern of AI
C. Determine what you're trying to accomplish and see which pattern(s) of AI fit best.
D. Apply every pattern to the project.

Answer: C

Explanation:
Identifying the specific goal of the project and matching it to the appropriate AI pattern(s) ensures the solution aligns with the problem's needs and maximizes effectiveness.

NEW QUESTION # 217
An AI-powered chatbot occasionally generates inappropriate or harmful responses despite strong training performance. The organization wants to reduce risks while maintaining usability. What is the most effective mitigation strategy for this issue?

A. Implement guardrails and content filters
B. Accelerate deployment cycles
C. Increase dataset size
D. Remove monitoring mechanisms

Answer: A

Explanation:
Guardrails control outputs and reduce harmful responses.

NEW QUESTION # 218
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