Try 12 free AWS AI Practitioner practice questions
Real exam-style questions taken word for word from the AWS AI Practitioner study guide. Three are below, with the full answer explanation. Enter your email and the full 12-question PDF is yours.
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Three questions to try right now
Work each one before you open the answer. These are the same style and depth as the AWS Certified AI Practitioner (AIF-C01) exam expects.
Question 1. A company wants to use large language models (LLMs) with Amazon Bedrock to develop a chat interface for the company's product manuals. The manuals are stored as PDF files. Which solution meets these requirements MOST cost-effectively?
- A. Use prompt engineering to add one PDF file as context to the user prompt when the prompt is submitted to Amazon Bedrock.
- B. Use prompt engineering to add all the PDF files as context to the user prompt when the prompt is submitted to Amazon Bedrock.
- C. Use all the PDF documents to fine-tune a model with Amazon Bedrock. Use the fine-tuned model to process user prompts.
- D. Upload PDF documents to an Amazon Bedrock knowledge base. Use the knowledge base to provide context when users submit prompts to Amazon Bedrock.
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Answer: D. A knowledge base retrieves only the most relevant chunks for each question, which keeps token usage and cost low while covering the full manual set. Stuffing one PDF limits coverage, stuffing all PDFs inflates token cost per call, and fine-tuning is expensive and unnecessary for retrieving reference content.
Question 2. A company has a generative AI application that uses a pre-trained foundation model (FM) on Amazon Bedrock. The company wants the FM to include more context by using company information. Which solution meets these requirements MOST cost-effectively?
- A. Use Amazon Bedrock Knowledge Bases.
- B. Choose a different FM on Amazon Bedrock.
- C. Use Amazon Bedrock Agents.
- D. Deploy a custom model on Amazon Bedrock.
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Answer: A. Amazon Bedrock Knowledge Bases add company context through retrieval at inference time without any training, which is the lowest-cost option. Switching models does not introduce company data, agents orchestrate multi-step actions rather than simply adding context, and deploying a custom model is far more expensive.
Question 3. A company uses an Amazon Bedrock large language model (LLM) in an application. During testing, the company observes different outputs from the same input. What is the MOST likely cause of this issue?
- A. The LLM is acting in a nondeterministic way.
- B. The guardrails of the LLM are not configured properly.
- C. The LLM has security vulnerabilities.
- D. The LLM is acting in a deterministic way.
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Answer: A. Producing different outputs for the same input is the hallmark of nondeterministic behavior, which comes from sampling-based generation. Deterministic behavior would produce identical output every time, so D is the opposite of what was observed. Misconfigured guardrails and security vulnerabilities would not specifically cause varied responses to the same prompt, so A is the most likely cause.
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