PMI CPMAI Exam : 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 manager is preparing to present data insights from a new AI-driven market analysis tool to the leadership team. The leadership team is particularly concerned about the tool's predictive accuracy and the interpretability of its results.
Which action should the project manager take?

A) Explain the tool's SHAP (Shapley additive explanations) values and their role in feature importance analysis.
B) Focus on the tool's MSE (mean squared error) and how it compares to baseline models.
C) Discuss the impact of hyperparameter tuning on the model's precision and recall metrics.
D) Highlight the tool's ROC-AUC (receiver operating characteristic area under the curve) and discuss its F1-score performance.

2. A government agency is operationalizing an AI system to optimize urban traffic flow that changes unexpectedly. The project manager needs to gather the required data from traffic cameras, sensors, and historical traffic patterns. What is an effective technique to meet the project manager's goals?

A) Applying dimensionality reduction to manage the complexity of traffic sensor data
B) Developing a probabilistic graphical model to infer latent traffic scenarios
C) Utilizing data augmentation to increase the diversity of traffic scenarios
D) Implementing real-time data synchronization to ensure up-to-date traffic analysis

3. You have been brought on to manage a recognition project, specifically an image recognition project, for an Autonomous Retail application. You know that you need to make sure you have sufficient data for this project. What's the best way to approach this?

A) Take inventory of all data your team has and use the relevant data
B) Take inventory of all data your company has and use the relevant data
C) Take all the existing data you have and apply it to this project
D) Take all the data your company has as well as purchase additional external data

4. A company's leadership team has requested insights into the AI model's ability to support decision-making processes without requiring them to understand complex technical details.
Which step should the project manager take?

A) Discuss how ensemble methods improve the model's robustness.
B) Describe the model's backpropagation and gradient descent optimization.
C) Demonstrate how the model's output can be integrated and used in end-user systems.
D) Explain the role of neural network architectures in prediction accuracy.

5. A project manager is considering the feasibility of an AI solution for a project aimed at improving customer service response times. They need to decide whether the project requirements can be solved with existing technologies or whether AI is the best approach. Which principle do the project manager's activities represent?

A) Assessing scalability requirements
B) Evaluating cognitive alternatives
C) Identifying ethical concerns
D) Determining automation potential

Solutions: