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PMI CPMAI Exam Syllabus Topics:

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

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q108-Q113):

NEW QUESTION # 108
The growth of Big Data has led to a desire to be able to do more to process and extract more value from Big Data. Simply storing data and providing analytics is no longer enough anymore to remain competitive. To keep your organization competitive, you need to:

A. Make sure everyone on the team has an understanding of data, its connections to the organization, and how to extract value from big data to unleash it for competitive advantage.
B. Make sure the technical team has deep understanding of big data and how best to extract value from big data to unleash it for competitive advantage.
C. Make sure senior management has deep understanding of big data and how best to extract value from big data to unleash it for competitive advantage.
D. Make sure all senior leadership is data literate, understands the Vs of big data, data's connections to your specific team, and how to extract value from big data to unleash it for competitive advantage.

Answer: D

Explanation:
Ensuring all senior leadership is data literate and understands big data concepts and their relevance to the organization is critical for strategic decision-making and maintaining a competitive advantage.

NEW QUESTION # 109
You are working on the data engineering pipeline for the AI project and you want to make sure to address the creation of pipelines to deal with model iteration. What part of the pipeline best deals with this step?

A. ELT Pipeline
B. Data Acquisition / Ingest / Capture
C. Feature Engineering
D. Retraining Pipelines

Answer: D

Explanation:
Retraining pipelines are designed to handle continuous model iteration by automating data updates, model retraining, and deployment to maintain model performance over time.

NEW QUESTION # 110
An organization is to undertake a multi-pattern AI project. They want to build a robot that is able to roam the halls as well as converse with employees and answer basic questions.
What is the best approach for handling this project?

A. Run each pattern as its own project, with their own CPMAI phase iterations, data requirements, and project needs
B. Run each pattern in isolation, with separate teams
C. Run it as a hybrid approach and some phases are run separately while other phases are combined together
D. Run it as one project, combining teams, data requirements, and project needs

Answer: C

NEW QUESTION # 111
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?

A. Autonomous patterns and process automation
B. Decision tree and Random Forest approaches
C. Generative AI solutions for content generation
D. Image and object detection and recognition systems

Answer: C

NEW QUESTION # 112
A manufacturing company is using an AI system for quality control. The project manager needs to ensure data privacy and compliance with industry standards. Which initial approach will effectively address these requirements?

A. Developing a comprehensive data governance plan
B. Establishing a data privacy task force
C. Implementing advanced data encryption methods
D. Conducting regular data privacy audits

Answer: A

Explanation:
Developing a comprehensive data governance plan is the most effective initial approach because it defines how data is collected, stored, accessed, protected, retained, and monitored in alignment with privacy obligations and industry standards.

NEW QUESTION # 113
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