Free AWS AI Practitioner AWS AI Services Practice Test 2026 — AIF-C01 Questions

This free AWS AI Practitioner AWS AI Services practice test covers Amazon Bedrock, SageMaker, Q, Rekognition, Comprehend, Textract, Transcribe, Polly, Translate, Lex, and Personalize — when to use each managed AI service on AWS. Each question includes a detailed explanation with AWS service context — perfect for AIF-C01 exam prep.

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6 Free AWS AI Practitioner AWS AI Services Practice Questions with Answers

Sample Question 1 — AWS AI Services

A retail company wants to analyze customer reviews to determine the overall sentiment and categorize them by product feature. Which AWS service should they use to efficiently perform sentiment analysis and entity recognition?

  1. A. Amazon Comprehend (Correct answer)
  2. B. Amazon Rekognition
  3. C. Amazon Lex
  4. D. Amazon Polly

Correct answer: A

Explanation: Amazon Comprehend is designed for natural language processing tasks, including sentiment analysis and entity recognition. Amazon Rekognition is for image and video analysis, Amazon Lex is for building conversational interfaces, and Amazon Polly is for text-to-speech conversion.

Sample Question 2 — AWS AI Services

A financial institution needs to automate the extraction of data from scanned documents to streamline their loan processing. Which AWS service is most appropriate for this task?

  1. A. Amazon Textract (Correct answer)
  2. B. Amazon Rekognition
  3. C. Amazon Translate
  4. D. Amazon SageMaker

Correct answer: A

Explanation: Amazon Textract is specifically designed to extract text and data from scanned documents. Amazon Rekognition focuses on image and video analysis, Amazon Translate is for language translation, and Amazon SageMaker is for building, training, and deploying machine learning models.

Sample Question 3 — AWS AI Services

A company wants to implement a chatbot that can handle customer queries and provide personalized responses in multiple languages. Which combination of AWS services would best meet their needs?

  1. A. Amazon Lex and Amazon Comprehend
  2. B. Amazon Lex and Amazon Translate (Correct answer)
  3. C. Amazon Polly and Amazon Rekognition
  4. D. Amazon Comprehend and Amazon SageMaker

Correct answer: B

Explanation: Amazon Lex is used to build conversational interfaces, and Amazon Translate can translate text into multiple languages, making them ideal for a multilingual chatbot. Amazon Polly is for text-to-speech, and Amazon Rekognition is for image analysis, neither of which are directly applicable to this scenario.

Sample Question 4 — AWS AI Services

An e-commerce company wants to recommend products to users based on their browsing history. Which AWS service can provide a ready-to-use solution for personalized recommendations?

  1. A. Amazon Personalize (Correct answer)
  2. B. Amazon Forecast
  3. C. Amazon Comprehend
  4. D. Amazon Lex

Correct answer: A

Explanation: Amazon Personalize is specifically built to provide real-time personalized recommendations based on user data. Amazon Forecast is for time-series forecasting, Amazon Comprehend is for natural language processing, and Amazon Lex is for building conversational interfaces.

Sample Question 5 — AWS AI Services

A media company needs to automatically generate transcriptions for their video content to improve accessibility. Which AWS service is best suited for creating text transcriptions from audio content?

  1. A. Amazon Transcribe (Correct answer)
  2. B. Amazon Polly
  3. C. Amazon Rekognition
  4. D. Amazon Translate

Correct answer: A

Explanation: Amazon Transcribe is designed to convert speech to text, making it ideal for generating transcriptions. Amazon Polly is for text-to-speech, Amazon Rekognition is for image and video analysis, and Amazon Translate is for language translation.

Sample Question 6 — AWS AI Services

A healthcare provider wants to use machine learning to predict patient readmission rates. They have a team of data scientists but want to minimize the infrastructure management overhead. Which AWS service should they consider for building and deploying their models?

  1. A. Amazon SageMaker (Correct answer)
  2. B. AWS DeepLens
  3. C. Amazon Comprehend Medical
  4. D. AWS Lambda

Correct answer: A

Explanation: Amazon SageMaker provides a fully managed service for building, training, and deploying machine learning models, reducing infrastructure management overhead. AWS DeepLens is for deep learning with computer vision, Amazon Comprehend Medical is for extracting medical information from text, and AWS Lambda is for running code in response to events.

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