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PMI CPMAI Exam Syllabus Topics:

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

1. Recently your company has been getting a large number of spam emails and some employees have been clicking on these suspicious emails causing a headache for IT. The head of IT wants to create a more robust spam filter and your team has been tasked with this project. What type of algorithm would you select for this problem?

A) Binary (or Binomial) Classification
B) Regression
C) Clustering
D) Multiclass Classification

2. Senior management has tasked your group to analyze a data set to uncover insights into the data. What is the best approach to use to do this?

A) Data Integration
B) Data preparation
C) Data Governance
D) Data Mining or Data Analytics

3. Your team is working on a new project for finding the most optimal flow of warehouse robots on the warehouse floor. Which type of machine learning approach would be most appropriate to pick for this problem?

A) Supervised Learning
B) Reinforcement Learning
C) All would work equally well
D) Unsupervised Learning

4. Use cognitive technologies/AI when you can't code the rules or you can't scale easily with people or automation. As a good rule of thumb when deciding if AI is right for the project you should:

A) Decide if it's probabilistic or deterministic patterns. If it's probabilistic then go with the AI project.
B) See if simple rules work. If yes, then pick the right AI solution to solve the problem.
C) Decide if it's probabilistic or deterministic patterns. If it's deterministic then go with the AI project.
D) Decide if it's a statistics pattern. If it's statistical then go with the AI project.

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) Failure to identify applicable data regulations early on
C) Inadequate separation of cognitive and noncognitive software
D) Lack of clarity on the project's business objective

Solutions: