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

1. Clean, well-labeled datasets used for machine learning are partitioned into three subsets:
Training sets, Validation sets, and Test sets. As your team is doing this, what's the best way to split up this data?

A) Use the same data for all sets
B) Split by alphabetical order
C) Split by patterned subsampling
D) Split by random subsampling

2. Enhancing and cleaning data is an important action during which phase of CPMAI?

A) Phase VI
B) Phase III
C) Phase I
D) Phase IV
E) Phase II
F) Phase V

3. A team has started working on their first AI project and they are running this project like a traditional software development project. About two months into the project the team is hitting some major issues, and you're tasked with coming in to help manage this project. Immediately you realize that AI projects need to be treated like data centric projects.
What's the next best course of action?

A) Hire an entirely new team making sure there is at least one data scientist on this new team
B) Bring in data centric methodology best practices to get this project back on track
C) Hire an outside consulting firm to handle the technical aspects while you train the team yourself on data centric best practices
D) Get the existing team up to speed and make sure existing Agile approaches can support the AI effort

4. Your team is testing the NLP model they just created to make sure it's performing as expected.
Some of your team members want to move this model to production and move to the next iteration.
What's wrong with this workflow?

A) Model Evaluation requires continuous model evaluation, retraining, and operationalization
B) You need to make sure the AI Go/No Go questions have been addressed
C) Nothing is wrong with this workflow. You can move to the next iteration
D) Team members should not be able to move to new projects until senior management signs off

5. The confusion matrix measures how the algorithm performs for a binary classification activity. As your team is running tests to evaluate model performance, they are seeing the model is incorrectly categorizing flowers as trees.
Your model is provided the following:

A) True Positive results
B) False Positive results
C) True Negative results
D) False Negative results

Solutions: