PMI certification practice

CPMAI_V7 Practice Questions

Try 10 free CPMAI_V7 exam-style questions for Cognitive Project Management in AI (CPMAI)™+ v7. Check each answer and review the explanation and source references.

Exam code
CPMAI_V7
Provider
PMI
Free questions
10
Full set
100 questions
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Candidates pursuing the PMI Cognitive Project Management in AI CPMAI v7 certification complete the associated course before becoming eligible to schedule the examination. To make your preparation more effective, Cert Mage provides CPMAI_V7 sample Exam Questions that introduce the situational and knowledge-based style used to assess AI fundamentals, the CPMAI methodology, machine learning, data for AI, and the management of AI initiatives. The Practice Tests also include explanations that clarify how the methodology applies to practical AI projects. For deeper revision beyond the sample questions, the complete Cert Mage quiz is recommended for broader topic coverage and repeated practice.

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You're working with an inexperienced team and this is all their first AI project. You're trying to work on a supervised learning binary classification problem to determine if emails are spam or not. What is the best approach for this project?
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Enhancing and cleaning data is an important action during which phase of CPMAI?
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Your team is working on a new facial recognition application. Since this technology has the potential to be mis-used you think it's important to set guidelines for the proper use of this application and you want to make sure the AI system is built for some positive purpose. What area of Trustworthy AI does this best fall under?
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In the case that an algorithm you want to use isn't algorithmically explainable, AI systems should try to do the following:
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You're running an image recognition project and realize that you do not have enough data of a certain type of vehicle. What is the best course of action to get the additional labeled data you need?
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Your team is working on a project and is running into some issues. You need someone on the team who is able to solve problems in environments of uncertainty, can deal with failure, and has the math and data visualization skills needed to communicate the results with others so the issues can get resolved. What role would be most suited for this?
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Your team is working on an image recognition project, have collected the appropriate data for the project, and have picked a neural network algorithm. They are now ready to train their model. In which phase of CPMAI is this done?
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You are working on the data engineering pipeline for the AI project and you want to make sure to address the creation of pipelines to deal with model iteration. What part of the pipeline best deals with this step?
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In order for Supervised Learning approaches to work, they must be fed clean, well-labeled data that the system can use to learn from examples. But how do you get Labeled Data? As a team leader at a small startup, what approach would not be beneficial when trying to gather labeled data?
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Your team is working on an NLP model and has just operationalized the first model. Your team makes updates to the model, overwrites the original model, and puts this new model into operation. However, one of the teams using the model has seen a decrease in performance and is asking to use the original model. What critical error did your team make?
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