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| Section | Weight | Objectives |
|---|---|---|
| Data for AI | 13% | - Data preparation and preprocessing - DataOps concepts - Data strategy and governance |
| Machine Learning | 13% | - Algorithms and models (e.g., NLP, Computer Vision) - Deep Learning and Neural Networks - Supervised, Unsupervised, and Reinforcement Learning |
| Trustworthy AI | 9% | - Privacy and security - Transparency and explainability - Ethical considerations and bias |
| CPMAI Methodology | 41% | - Phase III: Algorithm Selection & Model Training
|
| Managing AI | 8% | - Risk management in AI projects - Managing AI project teams and resources - Stakeholder management |
| AI Fundamentals | 16% | - Concepts and terminology of Artificial Intelligence - AI capabilities and limitations - Types of AI and Machine Learning |
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NEW QUESTION # 102
A healthcare AI model achieves high predictive accuracy but lacks transparency in decision- making. Regulators require clear explanations for each prediction to ensure patient safety and trust. What is the primary risk of deploying this model as-is?
Answer: C
Explanation:
Lack of explainability may violate healthcare regulations and safety standards.
NEW QUESTION # 103
The growth of Big Data has led to a desire to be able to do more to process and extract more value from Big Data. Simply storing data and providing analytics is no longer enough anymore to remain competitive.
To keep your organization competitive, you need to:
Answer: B
NEW QUESTION # 104
A project team is currently evaluating an AI solution. They need to ensure the machine learning model provides the expected business benefits. Which critical factor should the project manager assess?
Answer: A
Explanation:
Alignment with key performance indicators is critical because it shows whether the machine learning model is delivering the intended business value, such as improved efficiency, better decisions, reduced cost, higher revenue, or improved customer outcomes.
NEW QUESTION # 105
A telecommunications company is adopting an AI-based customer service chatbot. They are concerned about potential quality issues affecting customer satisfaction. What should the project manager do?
Answer: C
Explanation:
From a project management framework (such as PMBOK), quality must be planned in, not inspected in.
When faced with potential quality risks before or during adoption, a project manager's standard first step is to establish a Quality Assurance (QA) Plan. This plan defines quality standards, testing metrics, success criteria, and how quality control will be executed throughout the project lifecycle.
NEW QUESTION # 106
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?
Answer: C
Explanation:
Legal/compliance ensures adherence to regulatory requirements.
NEW QUESTION # 107
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