PMI CPMAI real exam prep : Cognitive Project Management in AI (PMI-CPMAI)

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PMI CPMAI Exam Syllabus Topics:

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

1. A project team has completed the Data Preparation phase. The prepared dataset meets quality thresholds, but the effort consumed 60 percent of the total project budget.
What should the project manager do at this stage?

A) Conduct a go/no-go review that reassesses business value against remaining budget
B) Reduce the scope of the modeling phase to recover budget
C) Escalate the budget overrun to the change control board for approval
D) Continue to Data Modeling since the data quality objective was achieved

2. A machine learning model shows excellent performance on training data but significantly worse results on validation datasets. The team suspects the model memorizes patterns rather than generalizing effectively. Which technique should be applied to address this issue?

A) Increase training epochs indefinitely
B) Use cross-validation techniques
C) Increase model complexity
D) Remove validation data

3. A project team lacks sufficient labeled data for supervised learning but must still deliver a functional AI solution. Time constraints prevent extensive manual labeling. What is the most appropriate approach to continue development effectively?

A) Duplicate existing labeled data
B) Use unsupervised or semi-supervised learning methods
C) Ignore labels and proceed
D) Cancel the project

4. A project team has a modest dataset and is concerned that a single train-test split may produce an unreliable performance estimate.
What approach should the project manager recommend?

A) Apply k-fold cross-validation
B) Repeat training with different random seeds
C) Use the full dataset for both training and evaluation
D) Increase the proportion of data allocated to testing

5. An insurance company is selecting an AI approach to automate simple claim approvals for low- risk cases. The organization wants the system to take actions with minimal human intervention based on predefined policies. Which AI capability best fits?

A) Predictive analytics
B) Conversational
C) Autonomous systems
D) Hyperpersonalization

Solutions: