CLF-C02 Cloud Technology and Services Practice Question
A company wants to automatically detect and label objects in photos uploaded by users — such as identifying if a photo contains a person, a car, or an outdoor scene — without building their own machine learning model. Which AWS service provides this pre-built computer vision capability?
⚠ Common exam trap
Test-takers frequently confuse Amazon Rekognition with Amazon SageMaker, assuming SageMaker is the go-to for all AI/ML tasks, but SageMaker requires custom model building, whereas Rekognition provides pre-built computer vision capabilities out of the box.
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
✓
Amazon Rekognition
Amazon Rekognition is the correct choice because it is a fully managed, pre-trained computer vision service that can automatically detect and label objects, scenes, and faces in images without requiring any custom machine learning model development. It provides APIs for image analysis, including object and scene detection, which directly matches the requirement to identify if a photo contains a person, car, or outdoor scene.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon SageMaker
Why it's wrong here
Amazon SageMaker is a fully managed platform for building, training, and deploying custom machine learning models. It requires you to develop, train, and manage your own ML pipelines, which is overkill for simple, pre-built object and scene detection. The question specifically asks for a pretrained service that can identify objects in images without any ML training, and SageMaker would need custom model creation, not a one-call API.
- ✗
Amazon Comprehend
Why it's wrong here
Amazon Comprehend is a natural language processing (NLP) service that performs sentiment analysis, entity extraction, key phrase detection, and language classification on text. It cannot process images or detect visual content like objects or scenes. Using it for image analysis would be a fundamental mismatch, as its input is plain text, not pixel data.
- ✓
Amazon Rekognition
Why this is correct
Amazon Rekognition is a fully managed computer vision service that provides pre-trained models via a simple API. It can automatically detect objects, scenes, people, faces, and text in images and videos without requiring any custom training or infrastructure. This directly matches the requirement of 'pretrained' object and scene detection, making it the correct choice.
- ✗
Amazon Polly
Why it's wrong here
Amazon Polly is a text-to-speech service that converts written text into natural-sounding speech using deep learning models. It is an output service for audio generation, not an analysis service for images. It neither accepts image input nor performs any object or scene detection, so it is entirely unrelated to the use case.
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Same concept, more angles
1 more way this is tested on CLF-C02
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Variation 1. A company wants to use machine learning to automatically identify objects, scenes, and activities in images uploaded by users. Which AWS service should they use?
easy- A.Amazon Textract
- B.Amazon SageMaker
- ✓ C.Amazon Rekognition
- D.Amazon Comprehend
Why C: Amazon Rekognition is the correct service because it is specifically designed to analyze images and videos to identify objects, scenes, activities, faces, and text. It provides pre-trained machine learning models that can automatically detect these elements without requiring custom model training, making it ideal for the use case described.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This CLF-C02 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 CLF-C02 exam.