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AIF-C01 practice question: AWS managed AI services (2 of 2)

Fundamentals of AI and ML A free question from our original AIF-C01 practice exam. Try it, then open the answer to see why each option is right or wrong.

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A healthcare analytics firm's data science team wants to build, train and deploy its own machine learning models on its own data.

It needs managed notebooks, managed training and managed hosting for each step of the workflow, without running servers.

Which AWS service is designed for this?

Choose one answer.

  1. A. Amazon Bedrock, which gives API access to ready-made foundation models.
  2. B. Amazon Comprehend, which analyzes text with prebuilt language models.
  3. C. Amazon SageMaker AI, which builds, trains and deploys custom ML models.
  4. D. Amazon Rekognition, which analyzes images with prebuilt vision models.
Show the answer and explanation

Answer: C

  • A. Wrong: Bedrock is aimed at using foundation models through an API. It is not built to run the full workflow for the team's own custom models.
  • B. Wrong: Comprehend uses prebuilt models to analyze text. It does not let the team build and deploy its own models on its own data.
  • C. Right: Correct. SageMaker AI is a fully managed ML service where data scientists build, train and deploy models into a hosted environment. It covers every step of the workflow. Learn more: What is Amazon SageMaker AI? (opens in a new tab)
  • D. Wrong: Rekognition analyzes images with prebuilt models. It does not give the team a workflow for training models on its own data.

Explanation

Amazon SageMaker AI is the service for building, training and deploying custom machine learning models, with managed infrastructure for each step. The other options offer prebuilt AI, either as an API to foundation models or as ready-made analysis for text or images. This question tests knowing which service is for custom ML.

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