Download Cognitive project management in AI.CPMAI.ExamTopics.2026-01-15.68q.vcex

Vendor: PMI
Exam Code: CPMAI
Exam Name: Cognitive project management in AI
Date: Jan 15, 2026
File Size: 44 KB
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Demo Questions

Question 1
Your team is using a neural network algorithm to generate a Machine Learning Model. What specific artifacts need to be included? (Choose all that apply.)
  1. The algorithm code
  2. Supporting training data
  3. Bias-variance tradeoff
  4. Hyperparameter settings
Correct answer: ABD
Question 2
In the case that an algorithm you want to use isn’t algorithmically explainable, AI systems should try to do the following:
  1. Provide a means to have contestability of the algorithm selected
  2. Provide a means to interpret AI results so that cause and effect can be represented
  3. Provide a means to have a different team on the project
  4. Provide a means to reverse-engineer the algorithm to inspect its performance
Correct answer: B
Question 3
You have just joined a team and they are working on a new project. The project lead isn’t sure what type of technology should be used on this project - AI or a traditional software development approach. What is the best way to determine if you have the criteria for a good AI / ML Project?
  1. Evaluate whether the solution can be done with automation.
  2. Determine if the project fits within the scope, budget, and timeline set out.
  3. Determine whether the project has a cognitive technology component and meets a short-term need.
  4. Determine the long-term need for the organization and build the project to that long-term goal.
Correct answer: C
Question 4
You want to create a model to figure out if a customer would be likely to repurchase a certain item. The project owner doesn’t want you to create anything too complicated, and you have a limited data set to work with.
Which algorithm is the best choice given these constraints?
  1. Ensemble models
  2. Naive Bayes
  3. Neural Networks
  4. Generative AI
Correct answer: B
Question 5
Your team has created a model that is going to be used for monitoring systems and it needs to provide analysis on a weekly basis. What’s the most appropriate Model Operationalization approach?
  1. Batch prediction
  2. Real-time prediction
  3. Web service / Microservice
  4. Stream learning
Correct answer: A
Question 6
Your team is running a simulation-based optimization exercise to increase routing efficiency. Learning for this exercise is done through “trial and error”
Which type of machine learning approach is being leveraged for this exercise?
  1. Unsupervised Learning
  2. Reinforcement Learning
  3. Supervised Learning
  4. All would work equally well
Correct answer: B
Question 7
You’re in charge of marketing at your organization and you’ve been tasked with using AI to help create marketing images. What’s a good solution for this need?
  1. Generative AI solutions for content generation
  2. Image and object detection and recognition systems
  3. Autonomous patterns and process automation
  4. Decision tree and Random Forest approaches
Correct answer: A
Question 8
Your team is trying to determine which pattern best fits their AI problem. To do this the project team is running through the seven patterns of AI to figure out what pattern best applies to their problem.
Which of the following is the best approach?
  1. When in doubt, go with the patterns and anomalies pattern as all AI projects are about pattern matching.
  2. Determine what you’re trying to accomplish and see which pattern(s) of AI fit best.
  3. Apply every pattern to the project.
  4. When in doubt, don’t apply any pattern of AI
Correct answer: B
Question 9
You are working for a large multinational organization and have been assigned to a new project. For your new ML project, you need to make sure you’re managing data privacy and security as you’re working with sensitive customer data.
What critical security issues do you need to make sure you address? (Choose all that apply.)
  1. Compliance with Data Privacy Laws even if they are out of your physical jurisdiction
  2. Securing model data and metadata
  3. Securing data at rest
  4. Securely storing all data collected for training purposes
Correct answer: ABCD
Question 10
Your team was given a large dataset and has been tasked with organizing the data by type to make better insights from the results. You are facing problems with the approach that the previous project lead used which was a regression algorithm.
What type of algorithm is the best approach for this project?
  1. Multiclass Classification
  2. Regression
  3. Clustering
  4. Binary (or Binomial) Classification
Correct answer: C
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