This MLS-C01 practice question tests your understanding of modeling. 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.
Refer to the exhibit. A training job failed with the error shown. What is the most likely cause?
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.
The model architecture is incorrect
Why wrong: Architecture issues would not produce this error.
The training data contains missing values or outliers that cause numerical instability
Error indicates NaN or infinity in input.
The instance type does not have enough memory
Why wrong: Not a memory error.
The training job exceeded the maximum runtime
Why wrong: Different failure reason.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
The training data contains missing values or outliers that cause numerical instability
Option A is correct because the error explicitly states input contains NaN or infinity, indicating missing or invalid values in the training data. Option B is wrong because the error is about input values, not about memory. Option C is wrong because the error is from the training script, not from SageMaker capacity. Option D is wrong because the error is about input data, not about model architecture.
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.
The model architecture is incorrect
Why it's wrong here
Architecture issues would not produce this error.
The training data contains missing values or outliers that cause numerical instability
Why this is correct
Error indicates NaN or infinity in input.
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.
The instance type does not have enough memory
Why it's wrong here
Not a memory error.
The training job exceeded the maximum runtime
Why it's wrong here
Different failure reason.
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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Identify which MLS-C01 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
Modeling — This question tests Modeling — Read the scenario before looking for a memorised answer..
The correct answer is: The training data contains missing values or outliers that cause numerical instability — Option A is correct because the error explicitly states input contains NaN or infinity, indicating missing or invalid values in the training data. Option B is wrong because the error is about input values, not about memory. Option C is wrong because the error is from the training script, not from SageMaker capacity. Option D is wrong because the error is about input data, not about model architecture.
Identify which MLS-C01 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 20, 2026
This MLS-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 MLS-C01 exam.
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