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PMI CPMAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Managing AI | 8% | - Stakeholder management - Managing AI project teams and resources - Risk management in AI projects |
| Topic 2: Machine Learning | 13% | - Supervised, Unsupervised, and Reinforcement Learning - Algorithms and models (e.g., NLP, Computer Vision) - Deep Learning and Neural Networks |
| Topic 3: CPMAI Methodology | 41% | - Phase II: Data Identification & Curation
|
| Topic 4: AI Fundamentals | 16% | - Types of AI and Machine Learning - Concepts and terminology of Artificial Intelligence - AI capabilities and limitations |
| Topic 5: Data for AI | 13% | - Data strategy and governance - Data preparation and preprocessing - DataOps concepts |
| Topic 6: Trustworthy AI | 9% | - Ethical considerations and bias - Privacy and security - Transparency and explainability |
PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions:
1. A project manager overseeing an AI project is concerned about potential data breaches. They need to establish a robust privacy and security plan. Where should the plan primarily focus to minimize risk?
A) Implementing multifactor authentication for all users
B) Updating security software and protocols regularly
C) Developing stringent access control policies
D) Conducting frequent vulnerability assessments and penetration testing
2. An IT services company is working on a project to develop an AI-based customer support system.
During data preparation, the project manager needs to clean and transform customer interaction logs. What is an effective technique to handle any missing data?
A) Remove records with missing values if minimal.
B) Ignore missing data if it seems insignificant.
C) Duplicate existing data to fill in missing gaps.
D) Fill missing values with zeros without analysis.
3. An organization aims to improve transparency and trust in its AI systems. Stakeholders request documentation outlining model purpose, limitations, risks, and performance characteristics. Which artifact should the project manager ensure is created and maintained?
A) Source code repository
B) Deployment script
C) Model card
D) Data pipeline diagram
4. A project team is working on an AI solution that needs to be both scalable and compliant with various regulations. They need to ensure all cognitive components are thoroughly evaluated for ethical considerations. The team has identified multiple patterns for the project.
How should the team proceed?
A) Implement a robust compliance monitoring system for scalability.
B) Conduct a detailed ethical review of all cognitive components.
C) Ensure scalability by continuously updating the intelligent system.
D) Divide the project into iterations based on identified computerized schemes.
5. An aerospace company is integrating AI into their manufacturing process to enhance safety and efficiency. The project team needs to evaluate potential security threats to prevent unauthorized access to sensitive data. What is the highest risk?
A) Employing a proprietary software with no open-source review
B) Operationalizing a decentralized data storage system
C) Secure APIs and data flows by enforcing data governance
D) Implementing an AI model without regular data updates
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: A | Question # 3 Answer: C | Question # 4 Answer: B | Question # 5 Answer: B |




