Courseiva
Machine Learning Implementation and OperationsmediumMultiple SelectObjective-mapped

MLS-C01 Practice Question: Machine Learning Implementation and Operations

A company is using SageMaker Autopilot to automatically build ML models. They want to ensure that the generated models are reproducible. Which TWO settings should they configure?

⚠ Common exam trap

AWS often tests the misconception that enabling automatic feature engineering or using multiple trials inherently ensures reproducibility, when in fact only controlling randomness via a seed and fixing the data split guarantees identical results.

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

Set a random seed.

Setting a random seed (Option A) ensures that the stochastic processes in model training (e.g., weight initialization, data shuffling, and hyperparameter sampling) produce identical results across runs. SageMaker Autopilot uses algorithms like XGBoost and linear learners that rely on randomness; fixing the seed guarantees reproducibility of the final model.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Set a random seed.

    Why this is correct

    Random seeds make train/test split and model initialization deterministic.

  • Specify a validation split.

    Why this is correct

    Manually specifying validation split ensures consistent data split.

  • Use multiple trials.

    Why it's wrong here

    Multiple trials introduce randomness; for reproducibility, use a single trial.

  • Enable early stopping.

    Why it's wrong here

    Early stopping can vary based on convergence; does not guarantee reproducibility.

  • Enable automatic feature engineering.

    Why it's wrong here

    Automatic feature engineering may produce different features across runs.

About these practice questions

This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →

How Courseiva writes practice questions · Editorial policy

JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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.