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

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PMI CPMAI Exam Syllabus Topics:

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

1. An AI project for a financial technology client is at risk due to potential inaccuracies in data aggregation. What is the first step the project manager should take to mitigate the risk?

A) Create a data visualization.
B) Evaluate the data freshness and relevance.
C) Understand the data characteristics.
D) Delete the suspicious data manually.

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

3. You're being told by upper management that you need to manage a new AI project. You need to determine the AI project fit to make sure you're actually solving a real business problem. During phase I: Business Understanding, you should consider at least one of the following (Choose all that apply):

A) Explores a proof of concept for an AI project
B) Solves an already solved problem but does it better and cheaper
C) Enhance revenue
D) Solves a previously unsolved problem
E) Has the "cool" factor
F) Improve company competitiveness in the market

4. The growth of Big Data has led to a desire to be able to do more to process and extract more value from Big Data. Simply storing data and providing analytics is no longer enough anymore to remain competitive. To keep your organization competitive, you need to:

A) Make sure all senior leadership is data literate, understands the Vs of big data, data's connections to your specific team, and how to extract value from big data to unleash it for competitive advantage.
B) Make sure the technical team has deep understanding of big data and how best to extract value from big data to unleash it for competitive advantage.
C) Make sure senior management has deep understanding of big data and how best to extract value from big data to unleash it for competitive advantage.
D) Make sure everyone on the team has an understanding of data, its connections to the organization, and how to extract value from big data to unleash it for competitive advantage.

5. 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?

A) Unsupervised Learning
B) Supervised Learning
C) All would work equally well
D) Reinforcement Learning

Solutions: