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

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

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

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

3. You're testing your model and it is overly sensitive to the fluctuations of data and having trouble generalizing. What type of problem is this?

A) You have selected the wrong data
B) You have selected the wrong algorithm
C) You are overfitting the data
D) You are underfitting the data

4. Your team is working on an image recognition system to help identify plants. They have collected a large amount of data but need to get this data labeled.
Which phase of CPMAI is this done?

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

5. Senior management has tasked your group to analyze a data set to uncover insights into the dat

A) Data preparation
B) Data Integration
C) What is the best approach to use to do this?
D) Data Governance
E) Data Mining or Data Analytics

Solutions: