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PMI CPMAI Exam Syllabus Topics:

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

1. A project lead is trying to work on a supervised learning binary classification problem to determine if emails are spam or not. They are working with an inexperienced team and this is their first AI project. What is an effective approach the project lead should use?

A) Selecting a simple algorithm such as a Gaussian mixture model
B) Selecting a known neural network algorithm that works well for supervised learning approaches
C) Selecting an ensemble method if uncertain as to which algorithm provides the best performance
D) Selecting a simple algorithm such as Naive Bayes

2. You need to hire a data scientist to join your team. What skill sets should you be looking for when hiring and interviewing this person? (Choose all that apply.)

A) Strong math skills, especially in calculus and statistics
B) Understanding of algorithms
C) Understanding of tools and technologies for manipulating, collecting, and preparing large data sets
D) Critical thinking skills
E) Prompt engineering skills
F) Automation skills, especially around creating RPA bots

3. Data Engineering is 80%+ of most AI projects, so building a good Data Engineering Environment is key to AI Project Success. As the manager of this project, you need to make sure you have correct staffing needs. What's the most critical role to staff for in the Big Data / Data Engineering Environment?

A) Data Scientists
B) All roles are critical to staff in the Four different AI Tech environments
C) Data Engineering
D) Data Engineering and Data Scientists
E) Senior management

4. 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?

A) Perform Data Sampling
B) Perform Data Transformation & Multiplication
C) Purchase the data from a third party
D) Perform Data anonymization

5. Major factors for the project you are currently working on is around the training time, cost, and complexity of training your models. Which algorithm is not the best choice given these constraints?

A) Support Vector Machines (SVM)
B) Naive Bayes
C) Gaussian Mixture
D) Neural Networks

Solutions: