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PMI CPMAI Exam Syllabus Topics:

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

1. You're working on a project and are working with personally identifiable information (PII). What's the best approach to take when it comes to collecting and using this data?

A) If this data is not needed, use Data anonymization techniques to remove it before feeding to models
B) Use noise reduction techniques to reduce all forms of data noise
C) Implement a new data privacy policy
D) Store the data in a data warehouse

2. 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

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

4. Your team is working on an NLP model and has just operationalized the first model. Your team makes updates to the model, overwrites the original model, and puts this new model into operation. However, one of the teams using the model has seen a decrease in performance and is asking to use the original model. What critical error did your team make?

A) They did not have data governance in place
B) They did not have a model retraining pipeline that took into account models
C) They did not practice model versioning and keep all versions of the model
D) They did not practice model iteration and properly iterate on the model

5. A project manager is tasked with ensuring the transparency of an AI project's data selection process. The project involves integrating multiple data sources from various departments. What should the project manager do?

A) Create a comprehensive data catalog.
B) Develop a data visualization dashboard.
C) Implement advanced data encryption techniques.
D) Establish a cross-departmental data sharing agreement.

Solutions: