LATEST PMI CPMAI_V7 MOCK TEST, 100% CPMAI_V7 CORRECT ANSWERS

Latest PMI CPMAI_v7 Mock Test, 100% CPMAI_v7 Correct Answers

Latest PMI CPMAI_v7 Mock Test, 100% CPMAI_v7 Correct Answers

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Tags: Latest CPMAI_v7 Mock Test, 100% CPMAI_v7 Correct Answers, Valid CPMAI_v7 Study Materials, CPMAI_v7 Exam Prep, CPMAI_v7 Reliable Exam Labs

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PMI Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam Sample Questions (Q72-Q77):

NEW QUESTION # 72
Use cognitive technologies/AI when you can't code the rules or you can't scale easily with people or automation. As a good rule of thumb when deciding if AI is right for the project you should:

  • A. Decide if it's probabilistic or deterministic patterns. If it's probabilistic then go with the AI project.
  • B. Decide if it's a statistics pattern. If it's statistical then go with the AI project.
  • C. Decide if it's probabilistic or deterministic patterns. If it's deterministic then go with the AI project.
  • D. See if simple rules work. If yes, then pick the right AI solution to solve the problem.

Answer: A

Explanation:
The CPMAI Glossary contrasts automation (for deterministic, rule-based tasks) with AI (for probabilistic, learning-based tasks). As a rule of thumb, if a problem exhibits probabilistic patterns that can't be captured by fixed rules, then AI is the appropriate solution; deterministic problems are better handled by simple automation.


NEW QUESTION # 73
One of the key elements of a data-centric methodology is the data requirements phase. During CPMAI Phase II, several unexpected issues have developed and are now threatening the data collection efforts.
What course of action might make the issue worse?

  • A. See if you can purchase the data needed to continue with the project
  • B. See if you already have access to enough data to continue with the project
  • C. See if you can expand the scope to continue with the project
  • D. See if you can adjust the scope of this interaction to continue with the project

Answer: C

Explanation:
In Phase II: Data Understanding, CPMAI urges teams to rigorously assess data feasibility-asking whether the data is available, sufficient in quality, and properly aligned with business goals-and to perform a Go/No- Go decision before proceeding . Expanding project scope in the face of data issues violates the methodology's iterative, scope-controlled approach. Instead, CPMAI recommends either down-scoping (Option C), verifying existing data sufficiency (Option B), or identifying necessary data sources (Option D) to resolve issues without amplifying risk.


NEW QUESTION # 74
Data Engineering is 80%+ of most AI projects, so building a good Data Engineering Environment is key to AI Project Success. As the manager of this project, you need to make sure you have correct staffing needs.
What's the most critical role to staff for in the Big Data / Data Engineering Environment?

  • A. All roles are critical to staff in the Four different AI Tech environments
  • B. Senior management
  • C. Data Engineering
  • D. Data Scientists
  • E. Data Engineering and Data Scientists

Answer: C

Explanation:
CPMAI underscores that preparing and managing data pipelines is foundational: in Phase III: Data Preparation, teams "create a reusable data pipeline to collect, ingest, and prepare data for training" and for inference . Ensuring these pipelines exist and are maintained falls squarely to Data Engineering specialists.
While data scientists leverage these pipelines for modeling, the dedicated Data Engineering role is the single most critical hire to support a Big Data environment.


NEW QUESTION # 75
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?

  • A. Autonomous patterns and process automation
  • B. Generative AI solutions for content generation
  • C. Decision tree and Random Forest approaches
  • D. Image and object detection and recognition systems

Answer: B

Explanation:
Generative AI is defined in the CPMAI Glossary as "AI systems that create new data (e.g., text, images, music) based on patterns learned from existing data." Using Generative AI for content generation directly addresses the need to produce marketing images automatically.
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NEW QUESTION # 76
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 have a different team on the project
  • B. Provide a means to interpret AI results so that cause and effect can be represented.
  • C. Provide a means to reverse-engineer the algorithm to inspect its performance
  • D. Provide a means to have contestability of the algorithm selected

Answer: B

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 # 77
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