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[General] PMI CPMAI_v7 Exam | Reliable CPMAI_v7 Braindumps Ppt - Trustable Planform Supply

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【General】 PMI CPMAI_v7 Exam | Reliable CPMAI_v7 Braindumps Ppt - Trustable Planform Supply

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PMI Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam Sample Questions (Q76-Q81):NEW QUESTION # 76
Your team is starting a new facial recognition project and you want to ensure that the project is being done with Trustworthy AI in mind. At what phase of CPMAI would Trustworthy AI be considered?
  • A. Phase II
  • B. Phase V
  • C. Phase VI
  • D. All phases
  • E. None of the phases
  • F. Phase III
  • G. Phase I
  • H. Phase IV
Answer: D
Explanation:
Trustworthy AI is not confined to a single phase but is woven throughout the entire CPMAI lifecycle:
The CPMAI Exam Content Outline under Domain VI: Trustworthy AI specifies tasks such as "Apply ethical AI concepts throughout the development lifecycle," "Ensure compliance with privacy/security requirements," and "Implement transparency and explainability" at every stage .
The CPMAI Workbook's Task Group: Trustworthy AI Requirements (covering transparency, explainability, ethics, compliance, and responsible-AI frameworks) appears as an overarching set of artifacts and considerations that map back to multiple phases-beginning with Business Understanding and continuing through Model Operationalization .
Thus, Trustworthy AI considerations apply across all CPMAI phases.

NEW QUESTION # 77
Your team is running a forecasting project and wants to use previous user data to better predict future outcomes. However your team doesn't have access to all the data it needs. What's the best course of action?
  • A. Move ahead as planned and hope you get access to the data once you need it. Since you're using an iterative approach you can always go back to steps as needed later on.
  • B. Cautiously move forward knowing you may need to pause mid-project which is ok.
  • C. Move ahead as planned so you stay on time with your project.
  • D. Do not move forward until you have access to all the data you need.
Answer: D
Explanation:
During Phase I: Business Understanding, the Data Feasibility task explicitly mandates a Go/No-Go decision on data availability and access: "Do you have access to the data you need? If not, what do you need for access to the data? Mark as a 'NoGo.'" Projects should not proceed until all essential data access requirements are met to avoid wasted effort and unresolvable blockages down the line

NEW QUESTION # 78
You need to hire a data scientist to join your team. What skill sets should you be looking for when hiring and interviewing this person? (Select all that apply.)
  • A. Prompt engineering skills
  • B. Strong math skills, especially in calculus and statistics
  • C. Understanding of tools and technologies for manipulating, collecting, and preparing large data sets
  • D. Critical thinking skills
  • E. Automation skills, especially around creating RPA bots
  • F. Understanding of algorithms
Answer: B,C,D,F
Explanation:
In Phase I's AI Skills Assessment, CPMAI directs teams to "List the cognitive skills you have available" and to identify "What expertise and skills you have available to you that you can use for this project" as well as any skills gaps to address . The methodology-and the CPMAI Glossary's definition of a data scientist- emphasizes core competencies in:
Data Engineering & Preparation (manipulating, collecting, transforming large data sets) Critical Thinking (interpreting insights to align with business goals) Algorithmic Understanding (selecting and applying the right statistical or ML models) Mathematical Proficiency (especially statistics and calculus underpinning model creation) By contrast, prompt engineering (A) is a specialized role for LLM interactions, not a general data-science core competency; and RPA-centric automation skills (E) fall outside the CPMAI focus on cognitive/ML capabilities.
=========

NEW QUESTION # 79
Your team is working on an image recognition project, have collected the appropriate data for the project, and have picked a neural network algorithm. They are now ready to train their model.
In which phase of CPMAI is this done?
  • A. Phase II
  • B. Phase V
  • C. Phase VI
  • D. Phase IV
  • E. Phase III
  • F. Phase I
Answer: D
Explanation:
Phase IV: Model Development is explicitly where "Model Training / Model Building" occurs. This phase includes tasks for selecting modeling techniques, conducting hyperparameter optimization, and executing the actual training runs on the prepared datasets.

NEW QUESTION # 80
Recently, you implemented an augmented intelligence application at work to help employees do their job better. However, employees have been resistant to this change and aren't using the application as expected.
What could have been done better to get the team to feel comfortable with this technology and use it? (Select all that apply.)
  • A. Have the team that built the technology relay to employees this tool is to augment, and not replace their jobs.
  • B. Have upper management relay to employees this tool is to augment, and not replace their jobs.
  • C. Provide training for everyone to have all employees feel more comfortable using the technology even if they aren't using the technology yet.
  • D. Ask end users what information and technology they need to help them do their job better and build the tool to help with these pain points.
Answer: A,B,C,D
Explanation:
The Continuous Improvement and Respect for People principle in CPMAI stresses involving end users early- gathering their pain points (A), clarifying that AI will augment rather than replace roles (B & C), and providing thorough training to build confidence (D). Engaging stakeholders throughout the project lifecycle and prioritizing user-centered design are key to adoption.

NEW QUESTION # 81
......
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