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PMI CPMAI Exam Syllabus Topics:

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

1. A project team is assessing a customer dataset and finds that 22 percent of records have a null value in the primary address field, and several records list contradictory account open dates.
Which two data quality dimensions are most directly affected?

A) Completeness and consistency
B) Accuracy and uniqueness
C) Validity and accessibility
D) Timeliness and relevance

2. A city transportation department is deploying an AI model that adjusts traffic signal timing. The department is concerned that traffic patterns will shift seasonally and during major events. What is the best method to manage this risk after deployment?

A) Increase the training dataset size once before launch
B) Perform continuous monitoring and auditing for drift and performance degradation
C) Disable model updates to maintain consistent behavior
D) Rely on vendor guarantees instead of internal controls

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

4. You are working on the data engineering pipeline for the AI project and you want to make sure to address the creation of pipelines to deal with model iteration. What part of the pipeline best deals with this step?

A) ELT pipeline
B) Feature Engineering
C) Data Acquisition / Ingest / Capture
D) Retraining Pipelines

5. An aerospace company is in the data preparation phase of an AI project. The project team must verify data quality to make a go/no-go decision for model development. They need to integrate data from several sensors with different sampling rates. What is an effective method that helps to ensure data consistency?

A) Aggregating sensor data
B) Applying a real-time data synchronization protocol
C) Utilizing data interpolation methods
D) Developing a custom data integration framework

Solutions: