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PMI CPMAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Model Development and Iteration | - Model building and validation
| |
| Topic 2: Data for AI | - Data identification and governance
| |
| Topic 3: Data Preparation for AI | - Data cleaning and transformation
| |
| Topic 4: Identify Business Needs and Solutions | 26% | - Problem framing and business alignment
|
| Topic 5: AI System Testing and Evaluation | - Model evaluation and monitoring
| |
| Topic 6: AI Operationalization and Governance | - Deployment and lifecycle management
|
PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions:
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. Utilizing a multiformat data integration tool
- B. Depending only on manual entry for format standardization
- C. Applying a diversified data ingestion model
- D. Adopting a hybrid data preparation pipeline
- E. Implementing a data normalization process
Correct Answer: A,E 🗳️
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Creating machine learning models can be complicated. Your team wants to use tools called Automated Machine Learning (AutoML) to simplify the process. You know of another team that has used AutoML tools and it's saved the team a lot of time. However, what's the one area you should not have the AutoML tool help with?
- A. Automatic model assessment
- B. Automatic model selection
- C. Automatic algorithm selection
- D. Iterative modeling and evaluation
- E. Automatic hyperparameter tuning
Correct Answer: D 🗳️
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Your team is working on an image recognition project, have collected the appropriate data for the project, and have picked a neural network algorithm. They are now ready to train their model. In which phase of CPMAI is this done?
- A. Phase III
- B. Phase V
- C. Phase I
- D. Phase II
- E. Phase IV
- F. Phase VI
Correct Answer: E 🗳️
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An AI project team has identified a gap in their data knowledge and experience. They need to address this issue in order to proceed with their AI implementation. What is the effective solution?
- A. Engage in a comprehensive data immersion program to build internal capabilities.
- B. Deploy an adaptive data knowledge framework (ADKF) to bridge the expertise gap.
- C. Utilize an AI-specific data enhancement protocol to improve data quality.
- D. Hire an external data consultant to provide targeted guidance and training.
Correct Answer: D 🗳️
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A financial services firm is building an AI model to detect fraudulent transactions. Identifying and validating data sources is critical to the model's success. What is an effective method that helps to ensure data accuracy?
- A. Utilizing data lineage tools to track data origin and transformations
- B. Employing a federated database system for decentralized data access
- C. Setting up a batch processing system for data cleansing
- D. Implementing a blockchain-based ledger for transaction data
Correct Answer: A 🗳️
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