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

1. You're working on a computer vision application and realize that you do not have enough real world data for the project. You need additional data created to support your training needs.
Specifically, the images you need are of people in different poses. What is the best way to obtain this data?

A) Make use of this data from surveillance footage
B) Make use of Synthetic Training Data
C) Make use of this data by having employees pose in the positions required
D) Make use of data from different departments

2. Your organization has just rolled out a new image recognition system and is asking all employees to use it. It was trained using images from the ImageNet test set. After a few weeks, users are finding the results are not as expected and are asking for visibility into all the aspects of what went into building an AI system.
What area of Trustworthy AI is being addressed here?

A) Governed AI
B) AI Systemic Transparency
C) Explainable AI
D) Transparent AI
E) Responsible AI

3. You're working with petabytes of data and need to make this dataset more manageable. To do this, you want to reduce the number of variables under consideration.
What is the name for this process?

A) Gradient Descent
B) Multivariate regression
C) Data selection
D) Dimensionality Reduction

4. You are establishing the data requirements for the project. Which of the following tasks is the least likely to impact data requirements?

A) The volume of the data you collect
B) The quality of the data you collect
C) The location/source of your data collection
D) The makeup of your data team

5. During CPMAI Phase II of your project, your team is going through their data collection needs.
One team member wants to make use of pre-trained models while another member is adamantly against it.
As the project lead, what should you do?

A) Evaluate your data and see if using pre-trained models make sense. If so, have the team do research to find the ones that best suit your project.
B) Evaluate your data and see if using pre-trained models make sense. If so, have the team see what pre-trained models your company already owns and use those.
C) Evaluate your data and use only what you have and build all models in house.
D) Have one team build all models in-house and the other team use pre-trained models and see which team's models perform better.

Solutions: