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. An IT services company is developing an AI system to automate network security monitoring. The project manager needs to consider various factors to mitigate risks associated with false positives and false negatives. Which action should the project manager implement?

A) Establishing a continuous feedback loop with security
B) Operationalizing the nearest neighbor detection algorithms
C) Implementing a robust data security validation process
D) Conducting model combinations and trade offs

2. During CPMAI Phase II it's important to not only understand the sources of your data, but also what data is required for training as well as identifying the features that are required. When looking to gather data, what approach is best when determining how much data you need?

A) There is no correct approach
B) The "less is better" approach
C) The "more is better" approach
D) The "goldilocks" approach

3. An AI project team is in the process of designing a security plan. The team needs to consider various aspects such as transparency, explainability, and compliance with data regulations.
Which action should the project manager take?

A) Focus only on technical security measures, ignoring transparency.
B) Ensure the AI system's decisions are transparent and explainable.
C) Rely solely on encryption without considering other security aspects.
D) Assume compliance without reviewing current regulations.

4. During which phase of an AI project should you consider Trustworthy AI considerations?

A) Phase VI: Model Operationalization
B) Phase II: Data Understanding
C) Every Phase of the AI project
D) Phase I: Business Understanding

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

Solutions: