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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: CPMAI Methodology | 41% | - Phase VI: Iteration & Monitoring
|
| Topic 2: Data for AI | 13% | - Data strategy and governance - DataOps concepts - Data preparation and preprocessing |
| Topic 3: Managing AI | 8% | - Stakeholder management - Risk management in AI projects - Managing AI project teams and resources |
| Topic 4: Machine Learning | 13% | - Supervised, Unsupervised, and Reinforcement Learning - Deep Learning and Neural Networks - Algorithms and models (e.g., NLP, Computer Vision) |
| Topic 5: Trustworthy AI | 9% | - Ethical considerations and bias - Privacy and security - Transparency and explainability |
| Topic 6: AI Fundamentals | 16% | - Types of AI and Machine Learning - AI capabilities and limitations - Concepts and terminology of Artificial Intelligence |
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NEW QUESTION # 68
Which of the following best describes the technical definition of Machine Learning?
Answer: D
Explanation:
This is the classic technical definition of machine learning, emphasizing improvement in task performance through experience measured by a performance metric.
NEW QUESTION # 69
A hospital wants to develop a medical records system with the primary goal of minimizing or eliminating paper records. They have identified where the cognitive AI solution will be applied. In addition, business objectives have been quantified and key performance indicators (KPI) have been determined. What else needs to be done to progress to the next Cognitive Project Management for AI (CPMAI) phase?
Answer: A
Explanation:
Determining the project ROI helps confirm that the quantified business objectives and KPIs justify continuing the AI initiative. This supports the business case and provides a measurable basis for progressing to the next CPMAI phase.
NEW QUESTION # 70
Your team is trying to determine which pattern best fits their AI problem. To do this the project team is running through the seven patterns of AI to figure out what pattern best applies to their problem. Which of the following is the best approach?
Answer: A
Explanation:
Identifying the specific goal of the project and matching it to the appropriate AI pattern(s) ensures the solution aligns with the problem's needs and maximizes effectiveness.
NEW QUESTION # 71
A team preparing data for a churn model transforms raw timestamps into derived attributes such as days since last purchase and purchase frequency over 90 days.
What activity is being performed?
Answer: A
Explanation:
Feature engineering creates new input variables from raw data to expose relationships that models can learn more effectively. Derived behavioral attributes often provide substantially more predictive signal than the underlying raw timestamps.
NEW QUESTION # 72
A project manager is reviewing the performance of an AI model used for predictive analytics in sales. The model's accuracy is within acceptable limits; however, its precision is low.
What is the cause for the precision issue?
Answer: B
NEW QUESTION # 73
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