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| Section | Weight | Objectives |
|---|---|---|
| CPMAI Methodology | 41% | - Phase I: Problem Identification
|
| Data for AI | 13% | - Data strategy and governance - Data preparation and preprocessing - DataOps concepts |
| AI Fundamentals | 16% | - Types of AI and Machine Learning - Concepts and terminology of Artificial Intelligence - AI capabilities and limitations |
| Machine Learning | 13% | - Deep Learning and Neural Networks - Supervised, Unsupervised, and Reinforcement Learning - Algorithms and models (e.g., NLP, Computer Vision) |
| Managing AI | 8% | - Risk management in AI projects - Stakeholder management - Managing AI project teams and resources |
| Trustworthy AI | 9% | - Privacy and security - Ethical considerations and bias - Transparency and explainability |
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NEW QUESTION # 187
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?
Answer: A
Explanation:
PMI's trustworthy AI framing highlights governance, transparency, and accountability as essential ingredients for systems people can interpret and monitor. When third-party data feeds can change, the PMI-aligned approach is to establish governance and supplier controls that define data quality expectations, lineage, permitted uses, privacy constraints, and monitoring/audit mechanisms. This supports accountability by making data dependencies explicit and enabling early detection when upstream changes degrade model behavior.
NEW QUESTION # 188
Your model has been working fine for the last three months, however recently you notice the model's performance has greatly declined. What seems to have been overlooked in your workflow pipeline?
Answer: B
NEW QUESTION # 189
Your organization wants to keep an eye on AI systems for Governance purposes. What are the most crucial things to consider? (Select all that apply.)
Answer: A,C,E,G
NEW QUESTION # 190
Your team is tasked with selecting an algorithm for a supervised learning classification project.
Which algorithm might you choose?
Answer: D
Explanation:
K-nearest neighbor is a supervised learning algorithm used for classification tasks, making it suitable for supervised classification projects.
NEW QUESTION # 191
When building your model you need to make sure you're not only checking for performance and making sure the model is giving the expected results. You also need to make sure the model is accomplishing the business objective.
At what phase of CPMAI is this most appropriate to do this?
Answer: F
NEW QUESTION # 192
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