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PMI CPMAI Exam Syllabus Topics:

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

1. A project team is evaluating whether an AI initiative should proceed beyond discovery.
Stakeholders are aligned on objectives, but the team has not confirmed data access, quality, or legal constraints. What is the most appropriate next action?

A) Move directly to deployment planning
B) Conduct a go/no-go assessment using readiness criteria
C) Purchase additional compute infrastructure
D) Begin model development using sample data

2. A consulting firm is determining the feasibility of an AI project. They need to justify the use of AI over noncognitive solutions. The project manager has listed potential noncognitive alternatives.
What is an effective method to support an AI approach?

A) Emphasizing the simplicity and reliability of noncognitive solutions
B) Relying only on industry trends favoring AI adoption
C) Focusing on the novelty and technological AI appeal
D) Conducting a cost-benefit analysis comparing AI and noncognitive solutions

3. You are working with a dataset that has a high number of dimensions. You're running into issues because some dimensions don't have enough real examples to properly train the systems for predictable results. What's your best course of action?

A) Keep going as planned and the problem will eventually correct itself
B) Try to get additional data - at least 5 training examples for each dimension in the representation
C) Try to get additional information from project lead to see how many examples per dimension are needed
D) Try to improve the quality of your data through more preparation

4. You're running an AI project and want to speed up training of the model so that you can complete your current CPMAI iteration within the two-week timeframe the team has set. What's one approach to speed up model training?

A) Use data from a previous project
B) Use cloud-based technology
C) Use or extend a pre-trained model
D) Use Brute force method

5. In preparation for an AI solution transition, the project team needs to ensure compliance with data regulations and ethical standards. They must identify and address potential privacy and transparency issues before moving forward.
What is the outcome if these requirements are neglected?

A) Failure to gain stakeholder trust
B) Increased risk of regulatory penalties
C) Compromised data integrity
D) Delays in project implementation

Solutions: