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PMI CPMAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Managing AI | 8% | - Stakeholder management - Managing AI project teams and resources - Risk management in AI projects |
| Data for AI | 13% | - DataOps concepts - Data strategy and governance - Data preparation and preprocessing |
| Machine Learning | 13% | - Supervised, Unsupervised, and Reinforcement Learning - Algorithms and models (e.g., NLP, Computer Vision) - Deep Learning and Neural Networks |
| Trustworthy AI | 9% | - Transparency and explainability - Privacy and security - Ethical considerations and bias |
| CPMAI Methodology | 41% | - Phase I: Problem Identification
|
| AI Fundamentals | 16% | - Concepts and terminology of Artificial Intelligence - Types of AI and Machine Learning - AI capabilities and limitations |
PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions:
1. A healthcare organization is evaluating the operationalization of an AI-powered diagnostic tool.
The tool is expected to enhance diagnostic accuracy and speed, thereby reducing patient wait times. The project manager needs to prepare a business case to present to the board of directors. Which method will help to ensure a robust business case?
A) Drafting a detailed implementation roadmap
B) Conducting a stakeholder impact analysis
C) Developing a predictive analytics model
D) Performing a cost-effectiveness study
2. An AI project team has prepared the data and is ready to proceed with model development.
Which action should the project manager perform next?
A) Prepare a report on the model's scalability.
B) Document the performance metrics for the model.
C) Conduct a final assessment of the data quality.
D) Ensure go/no-go questions have well-defined answers.
3. A fintech AI project uses third-party data sources for credit risk modeling. The project manager is concerned about compliance and accountability if the external data quality changes. Which control best supports responsible and trustworthy AI delivery?
A) Only document model performance once at launch
B) Establish data governance and supplier controls, including auditability and monitoring
C) Remove all external data sources immediately
D) Allow each team to apply its own data definitions
4. You are working on the data engineering pipeline for the AI project and you want to make sure to address the creation of pipelines to deal with model iteration. What part of the pipeline best deals with this step?
A) Retraining Pipelines
B) ELT pipeline
C) Data Acquisition / Ingest / Capture
D) Feature Engineering
5. Your team is working on an AI enabled chatbot to be placed on the website. The goal of the chatbot is to be able to answer questions 24/7 to service clients around the globe. When evaluating your data, you realize you don't have enough data to train the model. What's the best course of action?
A) Ask your customer service team to generate additional data for you to use for the project
B) Research what Third-Party Models are available and purchase them to keep the project moving
C) Do not move forward with the project
D) Use the data that you have and keep the project moving
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: C | Question # 3 Answer: B | Question # 4 Answer: A | Question # 5 Answer: B |






