Latest CPMAI_v7 Exam Question - CPMAI_v7 New Study Questions
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PMI Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam Sample Questions (Q85-Q90):
NEW QUESTION # 85
Your organization wants to keep an eye on AI systems for Governance purposes. What are the most crucial things to consider? (Select all that apply.)
Answer: A,C,F,H
Explanation:
Continuous System monitoring (C): Phase VI's "Monitoring and maintenance plan" requires teams to define
"What continuous monitoring and management approach and tools will be used for the model in this iteration?" to ensure the model continues to provide expected results in operation .
Data source identification (D): In Phase II: Data Understanding, teams must "Describe Data," including "Data source formats" and "Training data identification," to maintain visibility into where the model's inputs originate-essential for governance and troubleshooting .
Human chain of accountability (F): The "Model Governance Framework" task directs project teams to document "Determination of Governance Team," identifying members who will serve as the "owners" of the model and be responsible for its usage, soliciting feedback, and addressing concerns-establishing a clear accountability structure .
Key Performance Indicators (KPIs) (G): Domain V's "KPI Measurement" task mandates that teams "Align model performance with business key performance indicators" and implement ongoing KPI evaluation as part of quality assurance, providing the metrics by which governance bodies assess model health and business impact .
Options A, B, E, and H fall outside the core ongoing governance activities defined in CPMAI v7. Continuous monitoring of deployed models, clear data lineage, defined human accountability, and KPI tracking are the pillars of robust AI governance.
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NEW QUESTION # 86
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?
Answer: E
NEW QUESTION # 87
In order for Supervised Learning approaches to work, they must be fed clean, well-labeled data that the system can use to learn from examples. But how do you get Labeled Data?
As a team leader at a small startup, what approach would not be beneficial when trying to gather labeled data?
Answer: B
Explanation:
The Data Labeling task in Phase III: Data Preparation specifies that teams should identify labeling methods such as using internal staff, contracting third-party labelers, leveraging pre-existing labeled datasets, or combining those modes. Soliciting end-users to label data falls outside these recommended approaches and introduces uncontrolled variability and quality issues .
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NEW QUESTION # 88
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?
Answer: A
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 # 89
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?
Answer: A
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 # 90
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