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AIF-C01 Practice Question: A machine learning engineer needs to choose a…
A machine learning engineer needs to choose a service to extract text from scanned PDF forms, including handwritten fields. Which AWS service is MOST appropriate?
⚠ Common exam trap
Candidates often confuse Amazon Rekognition's text detection (which can find text in images but not extract structured form data or handwriting) with Textract's specialized document analysis, or assume Transcribe handles any 'text' extraction due to its name.
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 Textract
Amazon Textract is specifically designed to extract text and data from scanned documents, including PDFs, and supports handwriting recognition via its 'forms' and 'tables' features. It uses machine learning to detect and extract printed text and handwritten content from form fields, making it the most appropriate choice for this use case.
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 Transcribe
Why it's wrong here
Amazon Transcribe converts speech audio to text, so it cannot read scanned PDF images or handwriting at all. It is tempting because it also performs text extraction, but from audio sources; Amazon Textract would be correct for document and handwriting OCR.
- ✓
Amazon Textract
Why this is correct
Amazon Textract uses optical character recognition with specialised handwriting recognition models, satisfying the scanned-form and handwritten-field constraints. Unlike Rekognition, which classifies images, Textract returns structured text and form key-value pairs directly. Its DetectDocumentText and AnalyzeDocument APIs handle both printed and handwritten content without custom model training.
- ✗
Amazon Comprehend
Why it's wrong here
Amazon Comprehend is designed for natural language processing (NLP) tasks, such as sentiment analysis, entity recognition, and key phrase extraction from *existing* text. It does not perform optical character recognition (OCR) or handwriting recognition from scanned documents. Consequently, it cannot extract text from scanned PDF forms or handwritten fields, which is the core requirement. It is tempting because it processes text, but its function is analysis, not initial extraction from images. Comprehend would be appropriate if the goal were to analyse the *content* of already digitised text.
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Amazon Rekognition
Why it's wrong here
Amazon Rekognition is designed for image and video analysis, not for extracting text from scanned PDF forms with handwritten fields. It lacks the optical character recognition (OCR) engine optimised for handwriting and structured form parsing that Amazon Textract provides. Rekognition would be tempting because it can detect text in images via its `DetectText` API, making it a correct choice for extracting printed text from photographs or screenshots, but it cannot handle the handwritten content or form layout required here.
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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.