2025 THE BEST 100% FREE CPMAI_V7–100% FREE PDF TORRENT | USEFUL COGNITIVE PROJECT MANAGEMENT IN AI CPMAI V7 - TRAINING & CERTIFICATION EXAM DUMPS

2025 The Best 100% Free CPMAI_v7–100% Free Pdf Torrent | Useful Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam Dumps

2025 The Best 100% Free CPMAI_v7–100% Free Pdf Torrent | Useful Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam Dumps

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PMI Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam Sample Questions (Q47-Q52):

NEW QUESTION # 47
Recently your company has been getting a large number of spam emails and some employees have been clicking on these suspicious emails causing a headache for IT. The head of IT wants to create a more robust spam filter and your team has been tasked with this project.
What type of algorithm would you select for this problem?

  • A. Regression
  • B. Binary (or Binomial) Classification
  • C. Multiclass Classification
  • D. Clustering

Answer: B

Explanation:
A spam filter must decide between exactly two categories-spam or not spam-making it a binary (or binomial) classification task. The CPMAI Glossary defines binary classification as "a classification task where data is categorized into one of two classes (e.g., spam vs. not spam)."
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NEW QUESTION # 48
You're working on a project and are working with personally identifiable information (PII). What's the best approach to take when it comes to collecting and using this data?

  • A. Use noise reduction techniques to reduce all forms of data noise
  • B. If this data is not needed, use Data anonymization techniques to remove it before feeding to models
  • C. Store the data in a data warehouse
  • D. Implement a new data privacy policy

Answer: B

Explanation:
Under CPMAI Phase III: Data Preparation, the Data Format task includes "Data anonymization" as a core activity to remove or mask PII when it is not required for modeling, thereby protecting privacy while retaining data utility.
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NEW QUESTION # 49
You are being tasked to manage an AI project at your company and you need to identify which project to start with. What's the best way to approach this?

  • A. Ask key stakeholders from all groups for input about their pain points.
  • B. Find a project that requires 100% accuracy in the results and start with that one.
  • C. Go through all possible scenarios to come up with the perfect first project.
  • D. Ask key stakeholders from your group and find a small problem that would have a big return on investment and start there.

Answer: D

Explanation:
In Phase I: Business Understanding, CPMAI directs teams to "determine business objectives" by engaging stakeholders to surface specific pain points, estimate time-to-ROI, and prioritize projects that deliver tangible business value quickly. Focusing on a narrowly scoped problem with high ROI ensures early success, builds momentum, and validates the AI methodology before tackling larger or more complex initiatives.
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NEW QUESTION # 50
Enhancing and cleaning data is an important action during which phase of CPMAI?

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

Answer: F

Explanation:
Phase III: Data Preparation is dedicated to all data-centric tasks, including cleaning ("Clean data") and enhancement ("Enhance & Augment data") of raw inputs so they're ready for model consumption.
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NEW QUESTION # 51
Your team is running a simulation-based optimization exercise to increase routing efficiency. Learning for this exercise is done through "trial and error." Which type of machine learning approach is being leveraged for this exercise?

  • A. Unsupervised Learning
  • B. Reinforcement Learning is defined in CPMAI as the paradigm where agents learn optimal actions via interactions labeled by reward/punishment signals-essentially a "trial and error" process. Domain III of the CPMAI Exam Content Outline covers "Design reinforcement learning approaches with appropriate agents and environments," confirming that simulation-based, trial-and-error optimization is the hallmark of Reinforcement Learning .
  • C. Supervised Learning
  • D. Reinforcement Learning
  • E. All would work equally well

Answer: B


NEW QUESTION # 52
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