AI0-001 AI Models and Data Engineering Practice Question
A retail company uses a machine learning model to predict daily sales. The model takes features like past sales, promotions, holidays, and weather data. Recently, the model's accuracy dropped significantly. The data engineer checks the data pipeline and finds that the weather data source changed from a free API to a new paid API that provides more detailed data. The new data includes additional attributes like humidity and wind speed, but the existing pipeline only ingests temperature and precipitation. Also, the time zone format changed from UTC to local time. The model was trained on the old format. Which action should the engineer take first to restore model performance?
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
✓
Transform the new data to match the old format (time zone and selected features) and retrain the model.
The immediate problem is the time zone change causing misalignment between training and inference data. Transforming the new data to match the old format ensures consistency. Retraining with all new features may introduce drift; reverting may not be possible; merging data without alignment causes inconsistency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add a new step to merge old and new weather data before feeding to the model.
Why it's wrong here
Merging without consistent formatting would still cause issues in the model input.
- ✓
Transform the new data to match the old format (time zone and selected features) and retrain the model.
Why this is correct
This aligns the data with the training pipeline, resolving the immediate mismatch.
- ✗
Revert to the old weather API.
Why it's wrong here
The old API may no longer be available or may have been deprecated.
- ✗
Retrain the model with the new data including all new features.
Why it's wrong here
Adding new features without aligning the time zone will still cause misalignment; also new features may not be well-understood.
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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.