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| Section | Weight | Objectives |
|---|---|---|
| Data for AI | - Data identification and governance
| |
| AI Operationalization and Governance | - Deployment and lifecycle management
| |
| AI Model Development and Iteration | - Model building and validation
| |
| Data Preparation for AI | - Data cleaning and transformation
| |
| AI System Testing and Evaluation | - Model evaluation and monitoring
| |
| Identify Business Needs and Solutions | 26% | - Problem framing and business alignment
|
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NEW QUESTION # 232
You're running an image recognition project and realize that you do not have enough data of a certain type of vehicle. What is the best course of action to get the additional labeled data you need?
Answer: D
Explanation:
Purchasing additional labeled data from a reputable third party is the most direct way to obtain the specific, high-quality data needed to improve model training when existing data is insufficient.
NEW QUESTION # 233
You want to create a model to figure out if a customer would be likely to repurchase a certain item. The project owner doesn't want you to create anything too complicated, and you have a limited data set to work with. Which algorithm is the best choice given these constraints?
Answer: B
Explanation:
Naive Bayes is a simple, efficient algorithm well-suited for small datasets and straightforward classification tasks like predicting customer repurchase likelihood.
NEW QUESTION # 234
You are working for a large multinational organization and have been assigned to a new project.
For your new ML project, you need to make sure you're managing data privacy and security as you're working with sensitive customer data. What critical security issues do you need to make sure you address? (Choose all that apply.)
Answer: A,B,C,D
Explanation:
Managing sensitive customer data requires comprehensive security measures, including compliance with data privacy laws regardless of location, securing both model data and metadata, protecting data at rest, and ensuring secure storage of all training data.
NEW QUESTION # 235
A project involves integrating AI systems across multiple departments, each with different access levels. This complex Al project has presented the project manager with significant issues related to data misuse. The project team has been focused on their ethics guidelines but continues to experience data misuse. The project involves different regional data protection regulations which further increases the complexity. What issue will cause these challenges to occur?
Answer: C
Explanation:
A detailed governance strategy is needed to define how data is accessed, used, shared, monitored, and controlled across departments and regions. Ethics guidelines alone are not enough when the project involves multiple access levels, potential misuse, and varying data protection regulations.
NEW QUESTION # 236
During CPMAI Methodology Phase IV: Model Development, which of the following is not done during this phase?
Answer: A
NEW QUESTION # 237
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