AIF-C01 Fundamentals of AI and ML Practice Question
A company is using Amazon Rekognition to detect objects in images. They need to detect custom objects that are specific to their domain. What should they do?
⚠ Common exam trap
Candidates often confuse Amazon Rekognition Custom Labels with SageMaker Object Detection, not realizing that Custom Labels is a managed service specifically designed for custom image analysis without requiring ML expertise.
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
✓
Use Amazon Rekognition Custom Labels
Amazon Rekognition Custom Labels allows you to train a custom model using your own labeled images to detect domain-specific objects that are not covered by Rekognition's built-in labels. This is the correct service for custom object detection without needing to build a model from scratch.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Amazon Rekognition's built-in labels
Why it's wrong here
Rekognition's built-in labels cover a fixed general-purpose taxonomy, so they cannot recognise domain-specific custom objects. It is tempting because it requires no training and works immediately, and would be correct when detecting common categories such as cars, pets or scenes without customisation.
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Use Amazon SageMaker Object Detection algorithm
Why it's wrong here
SageMaker Object Detection builds and trains a separate custom model, which is not how Rekognition is extended to detect custom labels. It is tempting because it offers full control over training data and architecture, and would be correct when hosting a bespoke detection model independently of Rekognition.
- ✓
Use Amazon Rekognition Custom Labels
Why this is correct
Rekognition Custom Labels trains a bespoke model on your own labelled images, so it detects domain-specific objects that the general-purpose Rekognition detector cannot recognise. This directly satisfies the requirement for custom, domain-specific object detection without building a model from scratch.
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Use Amazon Comprehend
Why it's wrong here
Comprehend performs natural language processing on text — sentiment, entities, key phrases — and cannot analyse image pixels at all. It is tempting because it also offers custom classification, but that trains on documents, not images; Rekognition Custom Labels is the service that learns domain-specific visual objects.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-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 AIF-C01 exam.