CLF-C02 Cloud Technology and Services Practice Question
A company wants to accelerate their machine learning workflows by using pre-trained foundation models for tasks like text generation and image creation without training models from scratch. Which AWS service provides access to pre-trained foundation models via API?
⚠ Common exam trap
Candidates often confuse Amazon SageMaker (a full ML lifecycle service) with Bedrock (a managed FM API service), or mistakenly think Amazon Rekognition or AWS DeepComposer provide general-purpose generative AI capabilities, when in fact they are specialized for narrow use cases.
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 Bedrock
Amazon Bedrock is a fully managed service that provides access to pre-trained foundation models (FMs) from leading AI providers like AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon via a single API. It enables you to build generative AI applications for tasks such as text generation and image creation without managing underlying infrastructure or training models 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.
- ✗
Amazon SageMaker
Why it's wrong here
Amazon SageMaker is a full-lifecycle machine learning service for building, training, and deploying custom models. It requires you to handle data preparation, algorithm selection, training jobs, and inference endpoints, which is far more involved than calling a pre-trained model API. Amazon Bedrock, by contrast, offers serverless access to foundation models that are already trained, so you don't need to manage any underlying infrastructure.
- ✗
Amazon Rekognition
Why it's wrong here
Amazon Rekognition is a narrow, purpose-built AI service that performs specific vision tasks such as detecting faces, objects, and text in images and videos. It does not provide a catalog of general-purpose foundation models or a way to invoke large language models via a unified API. Bedrock is the platform that gives you access to multiple foundation models from various providers, making Rekognition an incorrect answer here.
- ✓
Amazon Bedrock
Why this is correct
Amazon Bedrock is a fully managed service that provides serverless API access to a broad selection of foundation models from Amazon, Anthropic, Meta, Stability AI, Cohere, and AI21 Labs. Using APIs like InvokeModel, you can build generative AI applications—including text generation, image generation, and question answering—without provisioning or managing any model training or inference infrastructure. Because the scenario requires a platform for accessing pre-trained foundation models via API, Bedrock is the correct choice.
- ✗
AWS DeepComposer
Why it's wrong here
AWS DeepComposer is an experimental, educational service that teaches generative AI principles through music composition using a keyboard and pre-trained models. It is not designed for production workloads, does not expose a general-purpose API to foundation models, and is unrelated to enterprise generative AI application development. Bedrock is the scalable, production-ready service that offers API access to foundation models across multiple domains, so DeepComposer is not the right answer.
Go deeper
Related to this question
About these practice questions
This CLF-C02 question is part of Courseiva's 988-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 →
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.