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PMI CPMAI Exam Syllabus Topics:

Section	Weight	Objectives
Support Responsible and Trustworthy AI Efforts	15%	- Manage bias, risk, compliance, and societal impact - Establish ethical and governance frameworks - Ensure fairness, transparency, accountability
Identify Business Needs and Solutions	26%	- Evaluate feasibility and value of AI solutions - Define requirements, scope, and success criteria - Align AI initiatives with organizational strategy
Manage AI Model Development and Evaluation	16%	- Monitor performance, accuracy, and reliability - Oversee model design, training, and validation - Address model drift, explainability, and limitations
Identify Data Needs	26%	- Define data requirements and sources - Ensure data quality, privacy, security, and compliance - Plan data collection, storage, and infrastructure
Operationalize AI Solution	17%	- Deploy AI systems into production - Establish monitoring, maintenance, and improvement processes - Manage change, adoption, and governance post-launch

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q138-Q143):

NEW QUESTION # 138
In what way would you be using Generative AI if you used the results of the Generative AI solution to improve and accelerate your job?

A. As an Augmented Intelligence system
B. As a programmatic approach for automation
C. As an autonomous system removing the human from the loop
D. Used for Hyperpersonalization

Answer: A

Explanation:
Using Generative AI results to enhance and accelerate your work represents Augmented Intelligence, where AI assists and amplifies human capabilities without fully replacing human decision-making.

NEW QUESTION # 139
A team is getting ready to begin working on a ML project. They need to build a data preparation pipeline and someone on the team suggests they reuse the same pipeline they created for their last project.
What's wrong with this suggestion?

A. There is no issue. Pipelines can be reused as needed between projects.
B. Pipelines are pattern needs specific so as long as it's the same pattern then you can reuse the pipeline.
C. Pipelines are model operationalization need specific.
D. Pipelines are pattern and model need specific.

Answer: D

NEW QUESTION # 140
Your model is going to be used for continuous monitoring of machinery, with need for continuous, instant model predictions. What's the most appropriate Model Operationalization approach?

A. Stream learning
B. Batch prediction
C. Web service / Microservice
D. Real-time prediction

Answer: D

Explanation:
Real-time prediction enables continuous, instant model inference required for monitoring machinery, providing timely alerts and decision support without delay.

NEW QUESTION # 141
Creating machine learning models can be complicated. Your team wants to use tools called Automated Machine Learning (AutoML) to simplify the process. You know of another team that has used AutoML tools and it's saved the team a lot of time. However, what's the one area you should not have the AutoML tool help with?

A. Automatic algorithm selection
B. Automatic model selection
C. Iterative modeling and evaluation
D. Automatic hyperparameter tuning
E. Automatic model assessment

Answer: B

NEW QUESTION # 142
Your team is working on a project and is running into some issues. You need someone on the team who is able to solve problems in environments of uncertainty, can deal with failure, and has the math and data visualization skills needed to communicate the results with others so the issues can get resolved. What role would be most suited for this?

A. Project Manager
B. Data Engineer
C. Citizen Data Scientist
D. Data Scientist

Answer: D

Explanation:
Data scientists are skilled in handling uncertainty, problem-solving, math, and data visualization to analyze results and communicate findings effectively.

NEW QUESTION # 143
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