Courseiva
ML Model DevelopmenthardMultiple ChoiceObjective-mapped

MLA-C01 ML Model Development Practice Question

A company needs to detect bias in a pre-trained model before deployment. They want to compute metrics like disparate impact and equal opportunity difference. Which AWS service should they use?

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

SageMaker Clarify

About these practice questions

This MLA-C01 question is part of Courseiva's 835-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

Same concept, more angles

1 more way this is tested on MLA-C01

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. A company uses SageMaker Clarify to detect bias during training. They want to ensure that the trained model does not rely on a sensitive attribute like gender. Which Clarify feature should they configure?

medium
  • A.Clarify bias config with post-training bias metrics
  • B.Clarify with SageMaker Model Monitor
  • C.SHAP analysis
  • D.Clarify processing job with pre-training bias metrics
  • E.Bias report generation
JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This MLA-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 MLA-C01 exam.