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PMI CPMAI Exam Syllabus Topics:

SectionWeightObjectives
Identify Business Needs and Solutions26%- Align AI initiatives with organizational strategy
- Define requirements, scope, and success criteria
- Evaluate feasibility and value of AI solutions
Support Responsible and Trustworthy AI Efforts15%- Establish ethical and governance frameworks
- Ensure fairness, transparency, accountability
- Manage bias, risk, compliance, and societal impact
Operationalize AI Solution17%- Manage change, adoption, and governance post-launch
- Deploy AI systems into production
- Establish monitoring, maintenance, and improvement processes
Manage AI Model Development and Evaluation16%- Address model drift, explainability, and limitations
- Oversee model design, training, and validation
- Monitor performance, accuracy, and reliability
Identify Data Needs26%- Ensure data quality, privacy, security, and compliance
- Plan data collection, storage, and infrastructure
- Define data requirements and sources

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q17-Q22):

NEW QUESTION # 17
Enhancing and cleaning data is an important action during which phase of CPMAI?

Answer: E

Explanation:
Phase II of CPMAI is focused on data preparation, including enhancing and cleaning data to ensure quality input for model training.


NEW QUESTION # 18
An aerospace company is in the data preparation phase of an AI project. The project team must verify data quality to make a go/no-go decision for model development. They need to integrate data from several sensors with different sampling rates. What is an effective method that helps to ensure data consistency?

Answer: B

Explanation:
Utilizing data interpolation methods helps align sensor data collected at different sampling rates by estimating values at common time intervals. This improves consistency across sensor streams before making the go/no-go decision for model development.


NEW QUESTION # 19
Your team is tasked with selecting an algorithm for a supervised learning classification project.
Which algorithm might you choose?

Answer: C

Explanation:
K-nearest neighbor is a supervised learning algorithm used for classification tasks, making it suitable for supervised classification projects.


NEW QUESTION # 20
A project manager is overseeing the development of an AI system and is concerned about maintaining user privacy. The project involves collecting sensitive user data with potential legal and compliance issues to consider.
What should the project manager prioritize to help ensure the AI system adheres to privacy requirements?

Answer: A

Explanation:
Regular privacy impact assessments help identify how sensitive data is collected, processed, stored, and used, while evaluating associated privacy risks against applicable legal and regulatory requirements. This enables the project team to maintain ongoing compliance throughout the AI system's lifecycle.


NEW QUESTION # 21
Using machine learning and other cognitive approaches to understand how to take past / existing behavior and predict future outcomes or help humans make decisions about future outcomes using insight learned from past behavior / interactions / data is a core part to which pattern(s) of AI?

Answer: D

Explanation:
Using machine learning to analyze past behavior and predict future outcomes or assist decision- making is central to the Predictive Analytics & Decision Support pattern in AI.


NEW QUESTION # 22
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