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

1. Your team is working on a new loan decision model that takes a number of factors and data points into consideration and then automatically approves or denies a loan. After a month in operation someone does a review and notices that the system is denying a large number of loans from a certain demographic when all other factors from people in other regions (such as age, salary, and credit score) are the same.
What is most likely happening here?

A) Nothing is wrong, algorithmic decisions will never be 100%
B) Generative AI models hallucinating data results
C) Data privacy issues leading to data sharing concerns
D) Biased data sets leading to algorithmic discrimination

2. 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?

A) Get your Users to Do it
B) Find a source of already labeled data
C) Contract with Third Party Data Labeling Firms
D) Hire a Contractor Workforce

3. You are establishing the data requirements for the project. Which of the following tasks is the least likely to impact data requirements?

A) The makeup of your data team
B) The quality of the data you collect
C) The location/source of your data collection
D) The volume of the data you collect

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

5. Your team has been asked to summarize and highlight patterns in historical purchasing data, identifying prior performance metrics and patterns. What type of analytics is most appropriate to apply for this need?

A) Projective Analytics
B) Diagnostic Analytics
C) Descriptive Analytics
D) Predictive Analytics

Solutions: