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PMI CPMAI Exam Syllabus Topics:

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

1. A telecommunications company is adopting an AI-based customer service chatbot. They are concerned about potential quality issues affecting customer satisfaction. What should the project manager do?

A) Conduct regular performance reviews and updates based on customer feedback
B) Set up a dedicated team to monitor and address quality issues
C) Initiate a beta testing phase with a small group of customers
D) Develop a comprehensive quality assurance plan for the chatbot

2. Clean, well-labeled, datasets used for machine learning are partitioned into three subsets:
Training sets, Validation sets, and Test sets. As your team is doing this, what's the best way to split up this data?

A) Split by alphabetical order
B) Use the same data for all sets
C) Split by patterned subsampling
D) Split by random subsampling

3. You have been brought on to manage a recognition project, specifically an image recognition project, for an Autonomous Retail application. You know that you need to make sure you have sufficient data for this project. What's the best way to approach this?

A) Take inventory of all data your team has and use the relevant data
B) Take all the data your company has as well as purchase additional external data
C) Take inventory of all data your company has and use the relevant data
D) Take all the existing data you have and apply it to this project

4. A company's leadership team has requested insights into the AI model's ability to support decision-making processes without requiring them to understand complex technical details.
Which step should the project manager take?

A) Describe the model's backpropagation and gradient descent optimization.
B) Explain the role of neural network architectures in prediction accuracy.
C) Discuss how ensemble methods improve the model's robustness.
D) Demonstrate how the model's output can be integrated and used in end-user systems.

5. A project manager is tasked with overseeing the implementation of an AI model for financial forecasting. They need to ensure the model's predictions are reliable. If the model's error rate exceeds acceptable boundaries, what will occur next?

A) Higher than expected computational costs
B) Increased stakeholder confidence that the project team will correct
C) Reduced need for human oversight since additional AI models will be used
D) Operationalization delays due to model retraining

Solutions: