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PMI CPMAI Exam Syllabus Topics:

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

1. Your team is running a forecasting project and wants to use previous user data to better predict future outcomes. However, your team doesn't have access to all the data it needs. What's the best course of action?

A) Cautiously move forward knowing you may need to pause mid-project which is ok.
B) Move ahead as planned and hope you get access to the data once you need it. Since you're using an iterative approach you can always go back to steps as needed later on.
C) Do not move forward until you have access to all the data you need.
D) Move ahead as planned so you stay on time with your project.

2. An organization aims to improve transparency and trust in its AI systems. Stakeholders request documentation outlining model purpose, limitations, risks, and performance characteristics. Which artifact should the project manager ensure is created and maintained?

A) Source code repository
B) Model card
C) Deployment script
D) Data pipeline diagram

3. You are establishing the data requirements for the project. Which of the following tasks is the least likely to impact data requirements?

A) The volume of the data you collect
B) The quality of the data you collect
C) The makeup of your data team
D) The location/source of your data collection

4. You recently completed an image recognition project at your company that was focused on identifying different types of cars. You have now been assigned a new image recognition project that is focused on identifying different types of animals. You know you can shortcut model development by using a specific technique. What is this technique called?

A) Transfer Learning
B) Generative AI
C) Pre-Trained Models
D) Reinforcement Learning

5. Creating machine learning models can be complicated. Your team wants to use tools called Automated Machine Learning (AutoML) to simplify the process. You know of another team that has used AutoML tools and it's saved the team a lot of time. However, what's the one area you should not have the AutoML tool help with?

A) Automatic algorithm selection
B) Iterative modeling and evaluation
C) Automatic model selection
D) Automatic model assessment
E) Automatic hyperparameter tuning

Solutions: