This PMLE practice question tests your understanding of architecting low-code ml solutions. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses AutoML Tables to predict customer churn. The model's AUC is low. Which action is most likely to improve performance?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Use a different optimization objective
Why wrong: Wrong: Changing objective may not improve AUC and could degrade it.
Add more training data
Correct: More data generally improves model performance.
Increase the training budget to 10 hours
Why wrong: Wrong: More budget may help, but data quantity is more critical.
Remove features with low importance
Why wrong: Wrong: Could lose valuable information; feature selection is secondary.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Add more training data
Adding more training data often helps improve model performance. Increasing the training budget alone may not help if data is insufficient. Removing features with low importance could hurt. Changing the optimization objective may not directly improve AUC.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Use a different optimization objective
Why it's wrong here
Wrong: Changing objective may not improve AUC and could degrade it.
Add more training data
Why this is correct
Correct: More data generally improves model performance.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
Increase the training budget to 10 hours
Why it's wrong here
Wrong: More budget may help, but data quantity is more critical.
Remove features with low importance
Why it's wrong here
Wrong: Could lose valuable information; feature selection is secondary.
Common exam traps
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Identify which PMLE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Architecting low-code ML solutions — This question tests Architecting low-code ML solutions — Read the scenario before looking for a memorised answer..
The correct answer is: Add more training data — Adding more training data often helps improve model performance. Increasing the training budget alone may not help if data is insufficient. Removing features with low importance could hurt. Changing the optimization objective may not directly improve AUC.
Identify which PMLE exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 24, 2026
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.
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