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PMI Certified Professional in Managing AI Sample Questions:

1. A project manager is overseeing the quality assurance and quality control of an AI/machine learning (ML) model. The model has been trained and initial tests have shown promising results. However, the project manager is concerned about the long-term performance and reliability of the model in real-world scenarios.
What should the project manager do?

A) Establish continuous monitoring and feedback loops
B) Perform a comprehensive hyperparameter tuning
C) Implement additional data augmentation techniques
D) Set up cross-validation with a larger dataset

2. A financial services firm is integrating AI to enhance fraud detection. To oversee data evaluation, the project manager needs to ensure the integrity and accuracy of input data, including transaction histories and customer profiles.
Which method provides the results that address the requirements?

A) Applying a visualization generator to create data flow diagrams
B) Using a fact checklist to systematically verify data sources
C) Utilizing a prompt pattern to guide the AI model's training process
D) Implementing alternative approaches to process data differently

3. A telecommunications company is preparing data for an AI tool. The project team needs to ensure the data is in the right shape and format for model training. In addition, they are working with a mix of structured and unstructured data.
Which method will address the project team's objectives?

A) Separating structured and unstructured data into different databases
B) Using a hybrid storage system for both data types
C) Employing a data transformation tool to standardize formats
D) Converting unstructured data into structured formats

4. A logistics company is operationalizing an AI solution to optimize delivery routes. The project manager needs to gather up-to-date information on traffic patterns, delivery schedules, and vehicle performance.
Which method will integrate these diverse data types?

A) Adopting a federated data model
B) Implementing a real-time data processing framework
C) Building a unified data warehouse
D) Using an extraction, transformation, and loading (ETL) pipeline

5. A healthcare project manager is evaluating whether to implement an AI-powered diagnostic tool. The initial cost is US$500,000 with an expected return on investment (ROI) of 15% within the first year. The project needs to satisfy multiple stakeholders including hospital administrators and medical staff.
Which method will maximize a positive ROI for the AI implementation?

A) Monitoring AI model performance against key performance indicators
B) Acquiring alternatives to the AI solution as a contingency plan
C) Seeking verbal commitments from interested parties at each project phase
D) Ensuring all AI and non-AI components are integrated seamlessly

Solutions: