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PMI Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam Sample Questions (Q88-Q93):

NEW QUESTION # 88
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.)

A. Key Performance Indicators (KPIs)
B. ROI determination
C. Data source identification
D. AI System testing requirements
E. Vendor procurement methods
F. Algorithm selection
G. Human chain of accountability
H. Continuous System monitoring

Answer: A,C,G,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 # 89
An inexperienced team is training a neural network model on a desktop computer and this is taking a significant amount of time. What would you recommend to them to speed up model training?

A. Train the model over multiple desktop computers
B. Train the model on GPUs
C. Use a contractor to do the training portion
D. Break the dataset up into multiple smaller datasets and train the model on each of the smaller datasets over a desktop computer

Answer: B

Explanation:
Training deep neural networks on CPUs is very slow. CPMAI's Glossary highlights that tensor processing units (TPUs) and GPUs are specialized hardware accelerators explicitly recommended to "accelerate the training and inference of machine learning models" by parallelizing the heavy matrix operations in neural- network layers. Switching from desktop CPU training to GPU-based training can reduce training time by orders of magnitude.
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NEW QUESTION # 90
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. Reinforcement Learning
B. All would work equally well
C. Supervised Learning
D. Unsupervised Learning

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 # 91
You're creating an AI-enabled chatbot that is going to access user data. What areas related to data governance do you need to make sure you're addressing? (Select all that apply.)

A. Security Risks
B. Change Management Issues
C. Data Sharing challenges
D. Data Quantity Issues
E. Privacy Risks
F. Data Quality Issues
G. Business Risks

Answer: A,C,E,F

Explanation:
Domain IV: Data for AI - Task 2: Implementing Data Governance and Management mandates establishing data stewardship, management plans, lineage, and master-data practices. Core governance concerns include how data is shared (A), ensuring user privacy (B), guarding against breaches (E), and maintaining high data quality (F). Quantity or change-management issues are operational rather than governance controls.
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NEW QUESTION # 92
The team is evaluating where the sources of the data for training are. What phase of CPMAI are they in?

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

Answer: C

Explanation:
Phase II, Data Understanding, is explicitly focused on identifying data needs and sources-including
"Identify appropriate datasets for machine learning" and "Evaluate training data requirements" under the Managing the Data Understanding Phase tasks. This is the phase where teams determine where and how they will collect the training data .
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NEW QUESTION # 93
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New CPMAI_v7 Study Guide & New Guide CPMAI_v7 Files

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PMI Cognitive Project Management in AI CPMAI v7 - Training & Certification Exam Sample Questions (Q88-Q93):

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