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PMI CPMAI Exam Syllabus Topics:

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

1. A project manager meets with a customer for initial discussions about an upcoming project. At the end of the meeting, the customer asks the project manager for a rough estimate of the project duration. Based on her experience with three similar projects, the project manager provides an estimate of 8-10 months. What's wrong with this timeframe?

A) It's underestimating the project timeline by 3 months
B) It's not accounting for data preparation timelines
C) It's not accounting for potential project delays
D) It fits into a waterfall timeframe, but not an agile project timeframe

2. Your team is working on an image recognition system to help identify plants. They have collected a large amount of data but need to get this data labeled. Which phase of CPMAI is this done?

A) Phase II
B) Phase III
C) Phase V
D) Phase VI
E) Phase IV
F) Phase I

3. An organization is to undertake a multi-pattern AI project. They want to build a robot that is able to roam the halls as well as converse with employees and answer basic questions. What is the best approach for handling this project?

A) Run each pattern in isolation, with separate teams
B) Run it as one project, combining teams, data requirements, and project needs
C) Run it as a hybrid approach and some phases are run separately while other phases are combined together
D) Run each pattern as its own project, with their own CPMAI phase iterations, data requirements, and project needs

4. A team is retraining a model and creating a new version of that model. What's the most important thing for the team to have in place before doing this?

A) Model Governance
B) Model discovery
C) Model operations
D) Data operations

5. A company is operationalizing an AI system for automated customer service. The system appears to favor queries in one language over others, despite having been trained on a multilingual dataset. Which two issues should the project lead investigate? (Choose two.)

A) Check the distribution of training samples per language.
B) Determine whether the neural network architecture supports multilingual processing.
C) Evaluate the system's response times for different languages.
D) Examine whether the preprocessing techniques varied across languages.
E) Presume the dataset is at fault, without conducting a detailed analysis.

Solutions: