hardMultiple ChoiceObjective-mapped
PMLE Practice Question: A company serves a scikit-learn model on Vertex…
A company serves a scikit-learn model on Vertex AI Prediction but receives a 400 error with 'Prediction failed: Model evaluation error'. What is the most likely cause?
⚠ Common exam trap
Google Cloud often tests the misconception that a 400 error always indicates a client-side input format issue, but here the error message 'Model evaluation error' points to a server-side model loading failure due to version incompatibility, not the input data.
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
✓
The model uses a scikit-learn version not supported by Vertex AI
Vertex AI Prediction supports specific versions of scikit-learn for serving models. If the model was trained with a version that is not in the supported list (e.g., 0.19, 0.20, 0.22, 0.23, 0.24, 1.0, 1.1), the prediction endpoint will fail with a 'Model evaluation error' because the underlying runtime cannot load the serialized model (e.g., pickle or joblib file). This is the most likely cause of a 400 error when the input format is otherwise correct.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The input data format is incorrect
Why it's wrong here
Incorrect input usually gives a different error.
- ✗
The model was trained with a different framework
Why it's wrong here
Vertex AI supports scikit-learn natively.
- ✓
The model uses a scikit-learn version not supported by Vertex AI
Why this is correct
Version mismatch causes evaluation failure.
- ✗
The endpoint is overloaded and timing out
Why it's wrong here
Timeout errors are different from evaluation errors.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PMLE practice question is part of Courseiva's free Google Cloud 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 PMLE exam.