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PMI CPMAI Exam Syllabus Topics:

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

1. A company is operationalizing an AI system for automated customer service. The system appears to favor queries in one language over others, despite having been trained on a multilingual dataset. Which two issues should the project lead investigate? (Choose two.)

A) Determine whether the neural network architecture supports multilingual processing.
B) Presume the dataset is at fault, without conducting a detailed analysis.
C) Check the distribution of training samples per language.
D) Examine whether the preprocessing techniques varied across languages.
E) Evaluate the system's response times for different languages.

2. A healthcare AI model achieves high predictive accuracy but lacks transparency in decision- making. Regulators require clear explanations for each prediction to ensure patient safety and trust. What is the primary risk of deploying this model as-is?

A) Reduced system speed
B) Data duplication issues
C) Increased operational costs
D) Regulatory non-compliance

3. An AI project team needs to assess the feasibility of an AI solution. In order to proceed with the AI project, what should the project manager address?

A) Alignment with business objectives
B) Complexity of operationalization
C) Potential vendor costs
D) Projected data debt

4. Your organization wants to keep an eye on AI systems for Governance purposes. What are the most crucial things to consider? (Choose all that apply.)

A) Key Performance Indicators (KPIs)
B) Data source identification
C) ROI determination
D) Vendor procurement methods
E) AI System testing requirements
F) Continuous System monitoring
G) Algorithm selection
H) Human chain of accountability

5. A project manager is evaluating whether an AI model is ready for operationalization. The project team has ensured the model meets accuracy and performance requirements and has conducted extensive testing. However, uncertainty about the model's operationalization in different environments and its compliance with regulatory standards still exists. What should the team do next?

A) Evaluate the model's adaptability to diverse conditions.
B) Implement additional noncognitive solutions.
C) Consider retraining the model for better performance.
D) Reassess the project's data preparation phase.

Solutions: