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PMI CPMAI Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Fundamentals16%- AI capabilities and limitations
- Concepts and terminology of Artificial Intelligence
- Types of AI and Machine Learning
Topic 2: Trustworthy AI9%- Transparency and explainability
- Ethical considerations and bias
- Privacy and security
Topic 3: Managing AI8%- Managing AI project teams and resources
- Risk management in AI projects
- Stakeholder management
Topic 4: Data for AI13%- DataOps concepts
- Data preparation and preprocessing
- Data strategy and governance
Topic 5: Machine Learning13%- Deep Learning and Neural Networks
- Algorithms and models (e.g., NLP, Computer Vision)
- Supervised, Unsupervised, and Reinforcement Learning
Topic 6: CPMAI Methodology41%- Phase V: Operationalization
  • 1. Define success criteria and monitoring
  • 2. Plan for deployment and integration
- Phase IV: Model Evaluation
  • 1. Evaluate model performance against metrics
  • 2. Oversee AI/ML model QA/QC
- Phase I: Problem Identification
  • 1. Evaluate initial AI feasibility
  • 2. Identify business needs and solutions
- 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 VI: Iteration & Monitoring
  • 1. Retraining and model drift management
  • 2. Continuous monitoring and iteration

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PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions (Q172-Q177):

NEW QUESTION # 172
Your team is working on an AI system to provide a more personalized experience for customers on your website. What should the team do in regard to determining the pattern of AI with regards to the ROI of the project?

Answer: A

Explanation:
Defining the project's objective or desired ROI first guides the selection of the appropriate AI pattern, ensuring the solution aligns with business value and goals.


NEW QUESTION # 173
Your team is running a simulation-based optimization exercise to increase routing efficiency.
Learning for this exercise is done through "trial and error" Which type of machine learning approach is being leveraged for this exercise?

Answer: B

Explanation:
Reinforcement learning involves learning optimal actions through trial and error by interacting with the environment, making it suitable for simulation-based optimization.


NEW QUESTION # 174
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: B

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 # 175
During the initial phase of an AI project, the team is assessing project success criteria. The project manager discovers that the project may be violating some compliance rules.
What problem describes the issue the project team is facing?

Answer: B


NEW QUESTION # 176
Leadership wants a new HR system built that will better handle potential candidate matching. The project manager assigned to this project believes that the project is well-suited for AI, however they are unsure which pattern of AI this would be.
What should the project manager do?

Answer: C


NEW QUESTION # 177
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