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| Section | Weight | Objectives |
|---|---|---|
| Data Preparation for AI | - Data cleaning and transformation
| |
| AI Operationalization and Governance | - Deployment and lifecycle management
| |
| Identify Business Needs and Solutions | 26% | - Problem framing and business alignment
|
| AI System Testing and Evaluation | - Model evaluation and monitoring
| |
| AI Model Development and Iteration | - Model building and validation
| |
| Data for AI | - Data identification and governance
|
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NEW QUESTION # 182
Accompany wants to determine whether to move forward with an AI project. The project manager has answered and received approval for all questions on technology, data, and business feasibility. Which activity did the project manager perform?
Answer: C
Explanation:
A go/no-go assessment evaluates whether the AI project should proceed by confirming technology readiness, data feasibility, and business value. Approval across these areas indicates the project manager completed the decision checkpoint needed to move forward.
NEW QUESTION # 183
A project manager is considering the feasibility of an AI solution for a project aimed at improving customer service response times. They need to decide whether the project requirements can be solved with existing technologies or whether AI is the best approach. Which principle do the project manager's activities represent?
Answer: B
Explanation:
Evaluating cognitive alternatives means determining whether the project requirements truly need AI-based cognitive capabilities or can be addressed using existing technologies, traditional automation, or non-AI approaches.
NEW QUESTION # 184
A model achieves 97 percent accuracy during validation but performs poorly in production.
Investigation reveals that a feature in the training set was derived from information that becomes available only after the outcome occurs.
What issue does this describe?
Answer: D
Explanation:
Data leakage occurs when the training data contains information that would not be available at prediction time. This inflates validation performance because the model is effectively learning from the answer, and the advantage disappears once the model is deployed.
NEW QUESTION # 185
A deployed AI system meets all technical acceptance criteria, but six weeks after release, usage data shows that fewer than 10 percent of intended users are engaging with it.
What was most likely inadequate?
Answer: C
Explanation:
Technical success does not produce business value unless users adopt the system in their workflow. Adoption requires training, workflow integration, communication, and management of concerns about how the system affects existing roles.
NEW QUESTION # 186
The confusion matrix measures how the algorithm performs for a binary classification activity. As your team is running tests to evaluate model performance, they are seeing the model is incorrectly categorizing flowers as trees. Your model is provided the following:
Answer: A
Explanation:
Incorrectly categorizing flowers as trees represents false positives - instances where the model incorrectly predicts the positive class when it should not.
NEW QUESTION # 187
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