AIF-C01 Fundamentals of AI and ML Practice Question
Which TWO are best practices for model monitoring in production on AWS?
⚠ Common exam trap
The AIF-C01 exam often tests the misconception that retraining on a fixed schedule (e.g., daily) is a best practice, when in reality it should be event-driven based on drift or performance metrics.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Monitor input data drift
Monitoring input data drift is a best practice for detecting changes in the distribution of incoming features compared to the training data. This helps identify when the model's assumptions about the data are no longer valid, which can degrade performance. AWS services like Amazon SageMaker Model Monitor can automatically track and alert on data drift.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Disable logging to reduce latency
Why it's wrong here
Logging is essential for monitoring and debugging; disabling it hinders observability.
- ✗
Use only CPU instances
Why it's wrong here
Instance type choice is not directly related to monitoring.
- ✓
Monitor input data drift
Why this is correct
Data drift detection helps identify when the distribution of input data changes, affecting model accuracy.
- ✗
Retrain model daily
Why it's wrong here
Daily retraining is not a best practice without evidence of drift; it can be wasteful.
- ✓
Monitor prediction drift
Why this is correct
Prediction drift detects changes in model output distribution, indicating potential issues.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.