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PMI CPMAI Exam Syllabus Topics:

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

1. You're working with a small inexperienced team on a new ML project. Choosing the best algorithm with the best settings given the training and test data is proving to be very hard for them. You lack the critical data science resources available on your team, and can't wait weeks until a data science resource becomes available to join your team. What's your best course of action?

A) Find a citizen data scientist to help
B) Use an AutoML solution
C) Outsource the project ASAP
D) Put the project on hold until the resources needed become available

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

3. A project team is using a prompt engineering approach to improve AI/machine learning (ML) model outputs. They started with broad questions and then narrowed down the specific elements.
If the team had provided insufficient context, what would be the result?

A) The output would include higher accuracy.
B) The model would perform more efficiently.
C) The model would generate more creative outputs.
D) The responses would lack relevance.

4. An IT services company is operationalizing an AI-based customer service chatbot. The project manager needs to track the workflow of key resources such as natural language processing experts, cloud computing resources, and integration specialists. What will enable the project manager to visualize and manage the cadence of resource activities?

A) Implementing a balanced scorecard
B) Using a kanban board
C) Applying a critical path method
D) Conducting a root cause analysis

5. A project manager is evaluating an AI model's performance to determine its business impact. The model has shown high accuracy during testing but has not been implemented yet in a live environment. The project manager needs to decide what to assess to ensure the model's effectiveness. What should the project manager do?

A) Determine the scalability for future expansions.
B) Conduct a cost-benefit analysis of the model's implementation.
C) Evaluate the ethical implications of operationalizing the model.
D) Check if the training data represents real-world scenarios.

Solutions: