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

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

2. You're running an image recognition project and realize that you do not have enough data of a certain type of vehicle. What is the best course of action to get the additional labeled data you need?

A) Perform Data Transformation & Multiplication
B) Purchase the data from a third party
C) Perform Data Sampling
D) Perform Data Anonymization

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

4. Your team is ready to operationalize the model they have been working on. It's a model that is meant to be used on an "edge device", specifically a mobile phone and the user may sometimes be in remote locations without regular access to the internet.
What's the most important thing to consider here?

A) Make sure the model lives in a hybrid environment
B) Make sure the model is available over a cloud-based API
C) Make sure the model lives on the edge device so it can be used regardless of internet connection
D) Make sure that you can use Generative AI solutions on an edge device

5. Creating machine learning models can be complicated. Your team wants to use tools called Automated Machine Learning (AutoML) to simplify the process. You know of another team that has used AutoML tools and it's saved the team a lot of time. However, what's the one area you should not have the AutoML tool help with?

A) Automatic model selection
B) Iterative modeling and evaluation
C) Automatic model assessment
D) Automatic algorithm selection
E) Automatic hyperparameter tuning

Solutions: