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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: AI Fundamentals | 16% | - Types of AI and Machine Learning - AI capabilities and limitations - Concepts and terminology of Artificial Intelligence |
| Topic 2: Trustworthy AI | 9% | - Transparency and explainability - Privacy and security - Ethical considerations and bias |
| Topic 3: Machine Learning | 13% | - Algorithms and models (e.g., NLP, Computer Vision) - Deep Learning and Neural Networks - Supervised, Unsupervised, and Reinforcement Learning |
| Topic 4: Data for AI | 13% | - DataOps concepts - Data preparation and preprocessing - Data strategy and governance |
| Topic 5: Managing AI | 8% | - Stakeholder management - Risk management in AI projects - Managing AI project teams and resources |
| Topic 6: CPMAI Methodology | 41% | - Phase III: Algorithm Selection & Model Training
|
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NEW QUESTION # 75
You recently completed an image recognition project at your company that was focused on identifying different types of cars. You have now been assigned a new image recognition project that is focused on identifying different types of animals. You know you can shortcut model development by using a specific technique. What is this technique called?
Answer: B
Explanation:
Transfer Learning involves leveraging a model trained on one task (e.g., car recognition) and adapting it to a related task (e.g., animal recognition), significantly reducing development time and resources.
NEW QUESTION # 76
An energy technology company is in the data preparation phase of developing an AI model to predict equipment maintenance needs. The project manager is deciding how to handle data from multiple formats. What is an effective technique the project manager should use?
Answer: A
Explanation:
Schema mapping is effective when data comes from multiple formats because it aligns fields, structures, and relationships into a consistent format that the AI model can use during preparation and training.
NEW QUESTION # 77
Your team has built a new robot that roams the halls at your organization and helps with various things such as small deliveries. However, you notice that many employees are opting not to use the robot. When you ask them why they tell you that the robot looks "creepy" and they would rather not interact with it.
What's going on here?
Answer: D
NEW QUESTION # 78
A healthcare provider is operationalizing an AI tool to assist in diagnostic processes. To ensure robust model governance, they need to address data privacy and ethical considerations. What should the project manager do?
Answer: D
Explanation:
Developing a detailed privacy impact assessment helps identify, evaluate, and mitigate privacy and ethical risks before and during operationalization. For a healthcare diagnostic AI tool, this supports responsible data handling, regulatory compliance, patient protection, and strong model governance.
NEW QUESTION # 79
In what way would you be using Generative AI if you used the results of the Generative AI solution to improve and accelerate your job?
Answer: B
Explanation:
Using Generative AI results to enhance and accelerate your work represents Augmented Intelligence, where AI assists and amplifies human capabilities without fully replacing human decision-making.
NEW QUESTION # 80
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