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

1. You are working with a dataset that has a high number of dimensions. You're running into issues because some dimensions don't have enough real examples to properly train the systems for predictable results.
What's your best course of action?

A) Try to get additional data - at least 5 training examples for each dimension in the representation
B) Keep going as planned and the problem will eventually correct itself
C) Try to get additional information from project lead to see how many examples per dimension are needed
D) Try to improve the quality of your data through more preparation

2. You have just joined a team and they are working on a new project. The project lead isn't sure what type of technology should be used on this project - AI or a traditional software development approach. What is the best way to determine if you have the criteria for a good AI/ML Project?

A) Determine whether the project has a cognitive technology component and meets a short-term need.
B) Determine if the project fits within the scope, budget, and timeline set out.
C) Evaluate whether the solution can be done with automation.
D) Determine the long-term need for the organization and build the project to that long-term goal.

3. You are working on the data engineering pipeline for the AI project and you want to make sure to address the creation of pipelines to deal with model iteration. What part of the pipeline best deals with this step?

A) ELT Pipeline
B) Feature Engineering
C) Data Acquisition / Ingest / Capture
D) Retraining Pipelines

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

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

Solutions: