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PMI CPMAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data for AI | 13% | - Data strategy and governance - Data preparation and preprocessing - DataOps concepts |
| Topic 2: Managing AI | 8% | - Stakeholder management - Risk management in AI projects - Managing AI project teams and resources |
| Topic 3: CPMAI Methodology | 41% | - Phase V: Operationalization
|
| Topic 4: Trustworthy AI | 9% | - Transparency and explainability - Ethical considerations and bias - Privacy and security |
| Topic 5: AI Fundamentals | 16% | - Types of AI and Machine Learning - Concepts and terminology of Artificial Intelligence - AI capabilities and limitations |
| Topic 6: Machine Learning | 13% | - Deep Learning and Neural Networks - Algorithms and models (e.g., NLP, Computer Vision) - Supervised, Unsupervised, and Reinforcement Learning |
PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions:
1. 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) Adopting a hybrid data preparation pipeline
C) Implementing a data normalization process
D) Utilizing a multiformat data integration tool
E) Depending only on manual entry for format standardization
2. 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?
A) Binary (or Binomial) Classification
B) Multiclass Classification
C) Clustering
D) Regression
3. 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) Gathering historical customer interaction logs for training data
B) Using synthetic data generated from sample customer conversations
C) Integrating feedback from beta customers to refine the model
D) Developing a new script based on anticipated customer queries
4. A project manager at an IT services company needs to present a business case for adopting an AI-driven cost-benefit analysis tool. The objective is to demonstrate the tool's value compared to existing processes. Which method will meet the project manager's objective?
A) Using a decision tree to simulate various cost scenarios
B) Implementing a fuzzy logic system for preliminary evaluations
C) Developing a proof of concept to highlight efficiency gains
D) Creating a detailed heuristic-based comparison report
5. An aerospace company is evaluating whether their sensor data meets the requirements for an AI- based predictive maintenance system. The project team needs to ensure that the data's accuracy, resolution, and timeliness are adequate to predict equipment failures. Which method addresses the requirements?
A) Implementing a data governance framework to ensure compliance
B) Performing a data quality assessment focusing on precision and latency
C) Analyzing data completeness and conducting feature engineering
D) Evaluating the data schema and integrating additional data sources
Solutions:
| Question # 1 Answer: C,D | Question # 2 Answer: C | Question # 3 Answer: A | Question # 4 Answer: C | Question # 5 Answer: B |
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