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PMI CPMAI Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Managing AI	8%	- Risk management in AI projects - Managing AI project teams and resources - Stakeholder management
Topic 2: Data for AI	13%	- DataOps concepts - Data strategy and governance - Data preparation and preprocessing
Topic 3: Trustworthy AI	9%	- Ethical considerations and bias - Privacy and security - Transparency and explainability
Topic 4: AI Fundamentals	16%	- Concepts and terminology of Artificial Intelligence - AI capabilities and limitations - Types of AI and Machine Learning
Topic 5: CPMAI Methodology	41%	- Phase VI: Iteration & Monitoring 1. Continuous monitoring and iteration 2. Retraining and model drift management - Phase IV: Model Evaluation 1. Evaluate model performance against metrics 2. Oversee AI/ML model QA/QC - Phase V: Operationalization 1. Plan for deployment and integration 2. Define success criteria and monitoring - Phase III: Algorithm Selection & Model Training 1. Manage model training and configuration 2. Oversee AI/ML model technique selection - Phase II: Data Identification & Curation 1. Assess data readiness and quality 2. Identify data needs - Phase I: Problem Identification 1. Identify business needs and solutions 2. Evaluate initial AI feasibility
Topic 6: Machine Learning	13%	- Algorithms and models (e.g., NLP, Computer Vision) - Deep Learning and Neural Networks - Supervised, Unsupervised, and Reinforcement Learning

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q12-Q17):

NEW QUESTION # 12
An energy technology company is in the data preparation phase of developing an AI model to predict equipment maintenance needs. The project manager is deciding how to handle data from multiple formats. What is an effective technique the project manager should use?

A. Cross-validation
B. Data warehousing
C. Schema mapping
D. Data consolidation

Answer: C

Explanation:
Schema mapping is effective when data comes from multiple formats because it aligns fields, structures, and relationships into a consistent format that the AI model can use during preparation and training.

NEW QUESTION # 13
A project manager is defining the operationalization plan for a deployed model and must specify when retraining occurs.
What is the most effective approach?

A. Define performance thresholds that automatically trigger retraining review
B. Retrain when a stakeholder reports dissatisfaction with outputs
C. Retrain whenever new training data becomes available
D. Retrain on a fixed quarterly schedule

Answer: A

Explanation:
Threshold-based triggers tie retraining to measured degradation rather than arbitrary intervals, avoiding both unnecessary retraining and prolonged periods of poor performance. Monitoring metrics against defined thresholds is a core operationalization control.

NEW QUESTION # 14
You are leading a project to develop a new predictive maintenance solution. Together with your project team you determine your data needs, see if you have access to the data, and then begin working on the project. Which phase best describes the work you are performing?

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

Answer: B

Explanation:
Phase II of CPMAI focuses on understanding and preparing data needs, including data acquisition and assessment before model development begins.

NEW QUESTION # 15
Your organization wants to use Generative AI. What are examples of when Generative AI can and should be used? (Select all that apply.)

A. Data Augmentation for Training
B. Explainable Decision-support systems
C. Content Generation
D. Programmatic automated content generation
E. Human Augmentation
F. Virtual Avatars and Characters

Answer: A,C,D,E

NEW QUESTION # 16
Your team is trying to determine which pattern best fits their AI problem. To do this the project team is running through the seven patterns of AI to figure out what pattern best applies to their problem. Which of the following is the best approach?

A. Determine what you're trying to accomplish and see which pattern(s) of AI fit best.
B. When in doubt, go with the patterns and anomalies pattern as all AI projects are about pattern matching.
C. When in doubt, don't apply any pattern of AI
D. Apply every pattern to the project.

Answer: A

Explanation:
Identifying the specific goal of the project and matching it to the appropriate AI pattern(s) ensures the solution aligns with the problem's needs and maximizes effectiveness.

NEW QUESTION # 17
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