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Vce PMI CPMAI_v7 Files & Reliable CPMAI_v7 Exam Prep

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PMI Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam Sample Questions (Q42-Q47):

NEW QUESTION # 42
In the case that an algorithm you want to use isn't algorithmically explainable, AI systems should try to do the following:

A. Provide a means to reverse-engineer the algorithm to inspect its performance
B. Provide a means to have contestability of the algorithm selected
C. Provide a means to interpret AI results so that cause and effect can be represented.
D. Provide a means to have a different team on the project

Answer: C

Explanation:
Under Required AI Explainability Considerations, CPMAI mandates that when a chosen model is a "black- box" with limited native interpretability, teams must implement post-hoc interpretability techniques (e.g., feature#importance plots, surrogate models) to "interpret AI results so that cause and effect can be represented," ensuring stakeholders understand why the model makes its predictions.
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NEW QUESTION # 43
For AI projects the code and systems don't matter as much as the data. In fact, big data is what's powering much of this latest wave of AI. What's most important for your company to consider around data?

A. Understanding which algorithms are best for your data needs.
B. Collect enormous amounts of data - the more data the better.
C. Have team members that have experience, understanding of tools, and the ability to deal with massive volumes of data.
D. Because of almost-infinite storage and compute power, collect as much data as possible and deal with organizing it later.

Answer: C

Explanation:
CPMAI emphasizes that data is only as valuable as the team's ability to manage, prepare, and harness it effectively. In Phase I: Business Understanding, one of the first tasks under Assess Situation is an "AI Skills Assessment," which ensures that the project team has the right mix of experience and tooling expertise to handle data- intensive AI work. Without skilled data engineers and AI practitioners, even the largest datasets cannot be transformed into business value.
The Workbook's Task Group: Assess Situation in Phase I explicitly calls out "AI Skills Assessment" alongside resource and tooling considerations, highlighting that team capability is a foundational requirement for any data-centric initiative.
Furthermore, in Domain IV: Data for AI of the CPMAI Exam Content Outline, managing data fundamentals and Big Data concepts hinges on having personnel who can "apply Big Data approaches to enhance AI capabilities", which presupposes the presence of experienced data professionals.
Thus, the single most critical factor is ensuring you have team members with the right experience and tool expertise to handle and derive value from massive volumes of data.

NEW QUESTION # 44
Your team is working on a new project for finding the most optimal flow of warehouse robots on the warehouse floor. Which type of machine learning approach would be most appropriate to pick for this problem?

A. Unsupervised Learning
B. Reinforcement Learning
C. All would work equally well
D. Supervised Learning

Answer: B

Explanation:
Reinforcement Learning (RL) is specifically designed for sequential decision-making tasks where an agent interacts with an environment and learns optimal behaviors through trial-and-error and reward signals.
Optimizing robot paths on a warehouse floor-deciding which movements lead to higher throughput-is a classic RL use case.
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NEW QUESTION # 45
You've built your model and now need to see if it actually works as expected. In which phase of CPMAI is this done?

A. Phase IV
B. Phase VI
C. Phase III
D. Phase II
E. Phase I
F. Phase V

Answer: F

Explanation:
Phase V: Model Evaluation is dedicated to validating a trained model's performance against technical metrics and the business success criteria defined earlier. This phase encompasses tasks such as generating performance results, measuring KPIs, and deciding whether to retrain or proceed to operationalization.
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NEW QUESTION # 46
Your team is working on a project and is running into some issues. You need someone on the team who is able to solve problems in environments of uncertainty, can deal with failure, and has the math and data visualization skills needed to communicate the results with others so the issues can get resolved.

A. Citizen Data Scientist
B. Data Scientist
C. Data Engineer
D. Project Manager

Answer: B

Explanation:
CPMAI defines a Data Scientist as the role responsible for "formulating data-driven hypotheses, selecting and applying statistical algorithms, interpreting model results, and communicating insights to stakeholders," all of which require critical thinking under uncertainty, advanced mathematics, and strong data-visualization skills .
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NEW QUESTION # 47
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