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PMI CPMAI Exam Syllabus Topics:

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

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q163-Q168):

NEW QUESTION # 163
You're running an AI project and want to speed up training of the model so that you can complete your current CPMAI iteration within the two week timeframe the team has set.
What's one approach to speed up model training?

A. Use or extend a pre-trained model
B. Use data from a previous project
C. Use Brute force method
D. Use cloud-based technology

Answer: A

NEW QUESTION # 164
A deployed AI system meets all technical acceptance criteria, but six weeks after release, usage data shows that fewer than 10 percent of intended users are engaging with it.
What was most likely inadequate?

A. Model evaluation rigor
B. Organizational change management and user adoption planning
C. Data quality assessment
D. Infrastructure capacity planning

Answer: B

Explanation:
Technical success does not produce business value unless users adopt the system in their workflow. Adoption requires training, workflow integration, communication, and management of concerns about how the system affects existing roles.

NEW QUESTION # 165
A healthcare project manager is evaluating whether to implement an AI-powered diagnostic tool.
The initial cost is US$500,000 with an expected return on investment (ROI) of 15% within the first year. The project needs to satisfy multiple stakeholders including hospital administrators and medical staff.
Which method will maximize a positive ROI for the AI implementation?

A. Ensuring all AI and non-AI components are integrated seamlessly
B. Monitoring AI model performance against key performance indicators
C. Acquiring alternatives to the AI solution as a contingency plan
D. Seeking verbal commitments from interested parties at each project phase

Answer: B

NEW QUESTION # 166
In a complex healthcare project, a provider plans to implement AI for patient data analysis to improve diagnostic accuracy. The project involves the need for interoperability between the AI systems and existing healthcare databases. These databases contain sensitive patient information. The requirements involve strict ethical and legal regulations in various countries.
Which critical step must be performed?

A. Creating a regulatory impact report
B. Implementing privacy impact assessments
C. Performing a detailed financial risk analysis
D. Maintaining high prediction accuracy

Answer: B

Explanation:
Implementing privacy impact assessments is critical because the project involves sensitive patient data, interoperability with healthcare databases, and legal and ethical obligations across multiple countries. This helps identify privacy risks, compliance requirements, and safeguards before the AI system is implemented.

NEW QUESTION # 167
A retail organization wants to start an AI initiative because a competitor recently announced a machine learning platform. The project manager is asked to launch development immediately using an existing dataset.
What should the project manager do first?

A. Assemble a data science team and begin exploratory analysis
B. Assess the quality and completeness of the existing dataset
C. Procure a machine learning platform comparable to the competitor's
D. Define the specific business problem and measurable success criteria

Answer: D

Explanation:
The Business Understanding phase requires a clearly defined problem and quantifiable success criteria before any data or modeling work begins. Starting development in response to competitive pressure, without a defined business objective, leads to solutions that cannot be evaluated or justified.

NEW QUESTION # 168
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