PMI CPMAI Exam : 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. The team is working to build a data preparation pipeline for the conversational chatbot project.
Which phase of CPMAI is this done?

A) Phase I
B) Phase IV
C) Phase II
D) Phase V
E) Phase III
F) Phase VI

2. Your organization has just rolled out a new image recognition system and is asking all employees to use it. It was trained using images from the ImageNet test set. After a few weeks, users are finding the results are not as expected and are asking for visibility into all the aspects of what went into building an AI system. What area of Trustworthy AI is being addressed here?

A) Explainable Al
B) Governed AI
C) Transparent AI
D) AI Systemic Transparency
E) Responsible AI

3. A project manager needs to select an effective technique to address distinct outputs and objectives in AI/machine learning (ML) model training. What should the project manager use?

A) A fixed set of predefined prompts
B) A generic prompt template
C) A single comprehensive prompt for all tasks
D) A sequence of prompts tailored to each output

4. Your team is running a forecasting project and wants to use previous user data to better predict future outcomes. However, your team doesn't have access to all the data it needs. What's the best course of action?

A) Do not move forward until you have access to all the data you need.
B) Move ahead as planned and hope you get access to the data once you need it. Since you're using an iterative approach you can always go back to steps as needed later on.
C) Cautiously move forward knowing you may need to pause mid-project which is ok.
D) Move ahead as planned so you stay on time with your project.

5. An IT services company is working on a project to develop an AI-based customer support system.
During data preparation, the project manager needs to clean and transform customer interaction logs. What is an effective technique to handle any missing data?

A) Remove records with missing values if minimal.
B) Fill missing values with zeros without analysis.
C) Ignore missing data if it seems insignificant.
D) Duplicate existing data to fill in missing gaps.

Solutions: