AI0-001 Implementing AI Solutions Practice Question
An AI system performs anomaly detection on sensor data in a manufacturing plant. The model is deployed and running well. After two months, the plant installs new sensors that produce data with a different distribution. The anomaly detection starts failing with many false positives. Which action should the team take?
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
✓
Retrain the model using data from the new sensors and re-deploy
The model needs monitoring and retraining on data from the new sensors. This falls under model monitoring and lifecycle management in deployment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Retrain the model using data from the new sensors and re-deploy
Why this is correct
Retraining on the new distribution adapts the model to the changed sensor data, reducing false positives.
- ✗
Roll back the model to the previous version and ignore the new sensors
Why it's wrong here
Ignoring new sensors defeats the purpose of monitoring the whole plant; it's not a long-term solution.
- ✗
Increase the anomaly threshold to reduce false positives
Why it's wrong here
Increasing the threshold may reduce false positives but also reduce true positives, missing real anomalies.
- ✗
Use an ensemble of the old and a new model without retraining
Why it's wrong here
Ensembling without retraining on new data does not address the distribution shift; the old model still fails on new sensors.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA 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 AI0-001 exam.