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PMI CPMAI Exam Syllabus Topics:

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

1. A financial services firm is operationalizing an AI-driven fraud detection system. The project manager needs to ensure the tool complies with relevant data privacy laws while providing secure data access to only authorized personnel. What is an effective technique to address these requirements?

A) Implementing real-time data verification (RTDV) processes
B) Utilizing role-based access control (RBAC) to limit data access
C) Developing a comprehensive data classification policy (DCP)
D) Conducting a privacy impact assessment (PIA) to identify risks

2. In order for Supervised Learning approaches to work, they must be fed clean, well-labeled data that the system can use to learn from examples. But how do you get Labeled Data? As a team leader at a small startup, what approach would not be beneficial when trying to gather labeled data?

A) Hire a Contractor Workforce
B) Find a source of already labeled data
C) Get your Users to Do it
D) Contract with Third Party Data Labeling Firms

3. An aerospace firm is developing an AI system for predictive maintenance of their aircraft. The project team needs to define the required data to train the model. Which activity should the project manager implement?

A) Implementing data cleaning and preprocessing routines
B) Conducting a pilot test with a small dataset
C) Setting up real-time data streaming from aircraft sensors
D) Developing a comprehensive data collection strategy

4. In the case that an algorithm you want to use isn't algorithmically explainable, AI systems should try to do the following:

A) Provide a means to interpret AI results so that cause and effect can be represented
B) Provide a means to have contestability of the algorithm selected
C) Provide a means to have a different team on the project
D) Provide a means to reverse-engineer the algorithm to inspect its performance

5. Major factors for the project you are currently working on is around the training time, cost, and complexity of training your models. Which algorithm is not the best choice given these constraints?

A) Neural Networks
B) Naive Bayes
C) Support Vector Machines (SVM)
D) Gaussian Mixture

Solutions: