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PMI CPMAI Exam Syllabus Topics:

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

1. A financial services firm is assessing the success of a newly operationalized AI system for fraud detection. The project manager needs to evaluate the model against business key performance indicators. (KPIs). What is an effective method to help ensure the accuracy of this evaluation?

A) Consulting with external experts and auditors
B) Implementing a single comprehensive metric
C) Reviewing quarterly business financial reports
D) Utilizing a diverse set of validation techniques

2. An AI project must comply with strict data protection and industry regulations. The project manager needs to ensure all processes align with legal requirements throughout the lifecycle.
Which stakeholder is most critical to involve continuously?

A) Data engineer
B) Scrum master
C) Legal and compliance officer
D) UX designer

3. A telecommunications company is preparing its data for a new AI-driven customer service chatbot. The project manager needs to ensure the data is precisely formatted and cleaned before moving on to the model-building phase. Which principle does this represent?

A) Defining cognitive pattern recognition
B) Implementing phase-specific data augmentation
C) Conducting AI readiness assessments
D) Performing data preprocessing tasks

4. A financial institution is planning to use AI capabilities to detect fraudulent transactions. The project manager needs to ensure that all necessary requirements are met before proceeding.
What is a necessary initial task?

A) Determining the scalability of AI solutions for transaction monitoring
B) Assessing the ethical implications of using AI for fraud detection
C) Evaluating the accuracy of current fraud detection methods
D) Identifying the primary stakeholders and their needs

5. An inexperienced team is training a neural network model on a desktop computer and this is taking a significant amount of time. What would you recommend to them to speed up model training?

A) Use a contractor to do the training portion
B) Train the model over multiple desktop computers
C) Break the dataset up into multiple smaller datasets and train the model on each of the smaller datasets over a desktop computer
D) Train the model on GPUs

Solutions: