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

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

2. Your team is looking to develop an RPA bot to help with back-office processes such as data entry.
What type of bot should your team be creating?

A) Attended bot
B) Business Process Outsourcing
C) Unattended bot
D) RPA is not the right solution to this problem

3. An organization is to undertake a multi-pattern AI project. They want to build a robot that is able to roam the halls as well as converse with employees and answer basic questions.
What is the best approach for handling this project?

A) Run each pattern in isolation, with separate teams
B) Run each pattern as its own project, with their own CPMAI phase iterations, data requirements, and project needs
C) Run it as one project, combining teams, data requirements, and project needs
D) Run it as a hybrid approach and some phases are run separately while other phases are combined together

4. A project manager is reviewing the performance of an AI model used for predictive analytics in sales. The model's accuracy is within acceptable limits; however, its precision is low.
What is the cause for the precision issue?

A) The model is underfitting the validation data
B) The model is overfitting the training data
C) The training data is unbalanced
D) The feature selection process is flawed

5. During the initial phase of an AI project, the team is assessing project success criteria. The project manager discovers that the project may be violating some compliance rules.
What problem describes the issue the project team is facing?

A) Absence of a clear AI go/no-go assessment
B) Lack of clarity on the project's business objective
C) Inadequate separation of cognitive and noncognitive software
D) Failure to identify applicable data regulations early on

Solutions: