MLA-C01 ML Model Development Practice Question
A company wants to use SageMaker Clarify to analyze bias in their training data and model predictions. Which TWO types of bias can Clarify detect? (Choose TWO.)
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
✓
Pre-training bias
SageMaker Clarify can detect pre-training bias (in the data) and post-training bias (in the model predictions).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Algorithmic bias
Why it's wrong here
Clarify does not analyze the algorithm itself; it analyzes data and predictions.
- ✓
Pre-training bias
Why this is correct
Clarify analyzes data for bias before training.
- ✗
Inference bias
Why it's wrong here
Inference bias is covered under post-training bias, but Clarify's terminology is pre- and post-training.
- ✗
Deployment bias
Why it's wrong here
Deployment bias is not a standard term in Clarify.
- ✓
Post-training bias
Why this is correct
Clarify analyzes model predictions for bias after training.
Go deeper
Related to this question
About these practice questions
Courseiva writes every MLA-C01 question from scratch — 835 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
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.