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PMI CPMAI Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Trustworthy AI | 9% | - Privacy and security - Ethical considerations and bias - Transparency and explainability |
| AI Fundamentals | 16% | - Concepts and terminology of Artificial Intelligence - Types of AI and Machine Learning - AI capabilities and limitations |
| Managing AI | 8% | - Stakeholder management - Risk management in AI projects - Managing AI project teams and resources |
| Machine Learning | 13% | - Supervised, Unsupervised, and Reinforcement Learning - Deep Learning and Neural Networks - Algorithms and models (e.g., NLP, Computer Vision) |
| Data for AI | 13% | - Data preparation and preprocessing - Data strategy and governance - DataOps concepts |
| CPMAI Methodology | 41% | - Phase VI: Iteration & Monitoring
|
PMI Cognitive Project Management in AI (PMI-CPMAI) Sample Questions:
1. An IT services company is developing an AI-driven customer support chatbot. The project manager assembling the team needs to identify the data subject matter experts (SMEs) who can contribute effectively to the chatbot training and optimization. What expertise should the project manager look for to meet this objective?
A) Knowledge of long-short-term memory (LSTM) neural networks and success in handling long- term dependencies
B) Background in recurrent neural networks (RNNs) and effectiveness in sequential data processing
C) Experience with generative adversarial networks (GANs) and generating realistic synthetic data
D) Proficiency in convolution neural networks (CNNs) and their use in image recognition
2. An AI project must comply with strict data protection and industry regulations. The project manager needs to ensure all processes align with legal requirements throughout the lifecycle.
Which stakeholder is most critical to involve continuously?
A) Scrum master
B) Legal and compliance officer
C) Data engineer
D) UX designer
3. You're being told by upper management that you need to manage a new AI project. You need to determine the AI project fit to make sure you're actually solving a real business problem. During phase I: Business Understanding, you should consider at least one of the following (Choose all that apply):
A) Solves an already solved problem but does it better and cheaper
B) Improve company competitiveness in the market
C) Has the "cool" factor
D) Enhance revenue
E) Solves a previously unsolved problem
F) Explores a proof of concept for an AI project
4. An AI project team needs to assess the feasibility of an AI solution. In order to proceed with the AI project, what should the project manager address?
A) Complexity of operationalization
B) Alignment with business objectives
C) Potential vendor costs
D) Projected data debt
5. A team is getting ready to begin working on a ML project. They need to build a data preparation pipeline and someone on the team suggests they reuse the same pipeline they created for their last project. What's wrong with this suggestion?
A) Pipelines are model operationalization need specific.
B) Pipelines are pattern needs specific so as long as it's the same pattern then you can reuse the pipeline.
C) Pipelines are pattern and model need specific.
D) There is no issue. Pipelines can be reused as needed between projects
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: A,B,D,E | Question # 4 Answer: B | Question # 5 Answer: C |
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