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. A telecommunications company is preparing data for an AI tool. The project team needs to ensure the data is in the right shape and format for model training. In addition, they are working with a mix of structured and unstructured data. Which method will address the project team's objectives?

A) Employing a data transformation tool to standardize formats
B) Separating structured and unstructured data into different databases
C) Using a hybrid storage system for both data types
D) Converting unstructured data into structured formats

2. A company is using an AI model to screen job applications. Over time, the project team notices that the model disproportionately rejects applications from certain educational institutions. What is the first step the project manager should take?

A) Analyze the historical data for inherent biases against these institutions.
B) Incorporate a fairness constraint into the model's objective function.
C) Adjust the model's decision threshold for applications from these institutions.
D) Retrain the model with equal representation from all institutions.

3. A government agency is developing an AI system to predict infrastructure failures. The data team needs to ensure that the dataset includes historical maintenance records, environmental data, and equipment usage logs. However, they are encountering issues with data from multiple sources being in different formats. Which two methods should be applied to meet the data team's objectives? (Choose two.)

A) Applying a diversified data ingestion model
B) Depending only on manual entry for format standardization
C) Utilizing a multiformat data integration tool
D) Implementing a data normalization process
E) Adopting a hybrid data preparation pipeline

4. During the evaluation of an AI solution, the project team notices an unexpected decline in model performance. The model was previously achieving high accuracy but has recently shown increased error rates. Which action will identify the cause of the performance decline?

A) Analyzing the distribution of real world data for potential shifts
B) Increasing the amount of regularization to prevent overfitting
C) Reviewing recent changes made to the model's architecture and parameters
D) Checking for issues in the data preprocessing pipeline that may have introduced noise

5. The project team at an IT services company is working on an AI-based customer support chatbot.
To help ensure the chatbot functions effectively, they need to define the required data. Which method meets the project requirements?

A) Integrating feedback from beta customers to refine the model
B) Using synthetic data generated from sample customer conversations
C) Developing a new script based on anticipated customer queries
D) Gathering historical customer interaction logs for training data

Solutions: