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41 multiple-choice questions and 41 flashcards on Applications of Foundation Models, about 27% of the AWS Certified AI Practitioner AIF-C01 bank. Every one carries a written rationale.
Applications of Foundation Models is one of 5 chapters in CoStudy's AWS Certified AI Practitioner (AIF-C01) bank, and it holds 41 of the bank's 150 multiple-choice questions — roughly 27% of the total. That proportion is not arbitrary: chapters follow the certifying body's published exam outline, and the number of questions in each is set by that domain's published weight, so the share of your practice time this chapter takes matches the share of the real exam it accounts for.
Studying by chapter is worth doing once you have a diagnostic score. A single overall percentage tells you whether you are close; it does not tell you which domain is dragging. Working a weak chapter in isolation, and re-testing it in isolation, is the fastest way to move a score that has stalled — and it is why the mock exams in CoStudy report by domain rather than as one number.
10 questions drawn from this chapter, with the full rationale shown — the controlling principle behind the right answer, and why each wrong option tempts and fails.
Which combination BEST fits 'summarize a PDF, extract action items, and email the summary'?
Answer: A — Bedrock Agents with a KB and an SES action group
A) Correct — Agents orchestrate KB lookup + summarization + tool calls (SES action). B) TTS, wrong task. C) STT, wrong task. D) Classifier, not summarizer / emailer.
A company wants the FM to autonomously call internal APIs (e.g., check inventory, place orders). Which fits BEST?
Answer: B — Bedrock Agents with action groups and knowledge bases
A) Guardrails filter content but don't call APIs. B) Correct — Agents plan and invoke OpenAPI-defined action groups. C) OCR + A2I. D) Q Business is a chat over data, not an autonomous action orchestrator.
Which SageMaker feature offers pre-built foundation models and solution templates?
Answer: A — SageMaker JumpStart with model templates
A) Correct — JumpStart is the model + solution catalog you can deploy in a few clicks. B) Feature Store manages ML features. C) Data prep. D) Endpoint monitoring.
A team needs a custom medical-document search experience for clinicians. Which fits BEST?
Answer: D — Amazon Kendra with medical connectors
A) Extracts entities, not a search experience. B) Guardrails filter content, not retrieve. C) TTS. D) Correct — Kendra is intelligent enterprise search with medical / semantic ranking.
A media company wants to detect inappropriate content in user-uploaded photos and videos. Which fits BEST?
Answer: B — Amazon Rekognition Content Moderation
A) Textract handles documents. B) Correct — Rekognition Content Moderation flags nudity, violence, etc. in images and video. C) Toxicity is for text. D) Macie is for PII in S3.
Amazon Rekognition is BEST described as:
Answer: B — A managed vision service for images and video
A) RDS. B) Correct — labels, faces, moderation, PPE, text-in-image. C) Amazon Polly. D) Amazon Lex.
Which AWS service identifies objects, scenes, text, and faces in images and video?
Answer: B — Amazon Rekognition
A) Extracts forms/tables from documents. B) Correct — computer vision for images and video. C) Text NLP. D) TTS. E) Semantic search over enterprise docs.
A team wants to convert recorded customer-service calls into searchable text. Which fits BEST?
Answer: C — Amazon Transcribe with speaker diarization
A) TTS. B) Search over docs, but you still need STT first. C) Correct — call analytics, speaker diarization, PII redaction, custom vocabulary. D) Rekognition is vision, not audio.
Which BEST describes Amazon Rekognition?
Answer: A — A managed computer vision service for images and video
A) Correct — labels, faces, PPE, moderation, text-in-image, celeb recognition. B) Timestream. C) Polly Neural/Generative. D) Amazon Translate. E) SageMaker Feature Store.
Which AWS service is BEST for generating natural voice prompts in an IVR system?
Answer: C — Amazon Polly Neural or Generative voices
A) STT, opposite direction. B) Dialog manager, not synthesis. C) Correct — Polly synthesizes lifelike speech (Neural, Long-form, Generative voices). D) NLP, not TTS.
4 cards from the 41 in this chapter.
Amazon Q Business?
Connects to enterprise data (Salesforce, S3, etc.). Answers questions, generates content.
SageMaker Canvas?
No-code ML. Drag-drop interface for non-developers.
Amazon Polly?
Text-to-speech. Many voices, languages, neural TTS.
Amazon Q?
AI assistant for business and developers. Q Business, Q Developer.
These are a sample. The full Applications of Foundation Models chapter runs 82 items with per-chapter progress tracking, on the web and in the iOS app.
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