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PMI CPMAI Exam Syllabus Topics:

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

1. A healthcare AI model achieves high predictive accuracy but lacks transparency in decision- making. Regulators require clear explanations for each prediction to ensure patient safety and trust. What is the primary risk of deploying this model as-is?

A) Regulatory non-compliance
B) Increased operational costs
C) Reduced system speed
D) Data duplication issues

2. An AI project team with a manufacturing company needs to ensure data integrity before moving to model development. They discovered some data inconsistencies due to manual entry errors.
What is an effective method that helps to ensure data integrity?

A) Conducting regular audits of manually entered data
B) Implementing real-time data validation rules
C) Using machine learning algorithms to detect and correct errors
D) Automating data entry processes

3. You need to hire a data scientist to join your team. What skill sets should you be looking for when hiring and interviewing this person? (Choose all that apply.)

A) Strong math skills, especially in calculus and statistics
B) Prompt engineering skills
C) Understanding of algorithms
D) Understanding of tools and technologies for manipulating, collecting, and preparing large data sets
E) Critical thinking skills
F) Automation skills, especially around creating RPA bots

4. A company is evaluating whether to implement AI for a project. They have defined their business objectives and determined the AI capability they want to use. Which action will enable the project manager to move forward with the project?

A) Conducting a go/no-go assessment
B) Identifying the contingency procedures
C) Conducting a data quality assessment
D) Implementing a preliminary version of the AI solution

5. A team is getting ready to begin working on a ML project. They need to build a data preparation pipeline and someone on the team suggests they reuse the same pipeline they created for their last project. What's wrong with this suggestion?

A) There is no issue. Pipelines can be reused as needed between projects
B) Pipelines are pattern needs specific so as long as it's the same pattern then you can reuse the pipeline.
C) Pipelines are model operationalization need specific.
D) Pipelines are pattern and model need specific.

Solutions: