PMI CPMAI - Cognitive Project Management in AI (PMI-CPMAI)

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PMI CPMAI Exam Syllabus Topics:

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

1. A manufacturing company is using an AI system for quality control. The project manager needs to ensure data privacy and compliance with industry standards. Which initial approach will effectively address these requirements?

A) Establishing a data privacy task force
B) Developing a comprehensive data governance plan
C) Implementing advanced data encryption methods
D) Conducting regular data privacy audits

2. A project team at a healthcare provider is determining whether their patient records are adequate for an AI diagnostic tool. They need to validate that the data covers a broad spectrum of conditions and demographics. What is an effective method to assure data suitability?

A) Implementing a longitudinal data-gathering approach
B) Performing demographic analysis and stratifying patient data
C) Analyzing data variance and ensuring balanced sampling
D) Conducting a cross-sectional study on data diversity

3. A retail bank wants to reduce fraudulent transactions by detecting unusual card activity in near real time. Which AI capability should be used?

A) Hyperpersonalization
B) Predictive analytics
C) Autonomous systems
D) Conversational

4. 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) Develop a comprehensive quality assurance plan for the chatbot
D) Initiate a beta testing phase with a small group of customers

5. A company is using an AI model to screen job applications. Over time, the project team notices that the model disproportionately rejects applications from certain educational institutions. What is the first step the project manager should take?

A) Analyze the historical data for inherent biases against these institutions.
B) Retrain the model with equal representation from all institutions.
C) Incorporate a fairness constraint into the model's objective function.
D) Adjust the model's decision threshold for applications from these institutions.

Solutions: