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Amazon AWS Certified AI Practitioner Sample Questions:

1. Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?

A) Support for geospatial indexing and queries
B) Ability to perform real-time analysis on streaming data
C) Scalable index management and nearest neighbor search capability
D) Integration with Amazon S3 for object storage

2. A company wants to develop a large language model (LLM) application by using Amazon Bedrock and customer data that is uploaded to Amazon S3. The company's security policy states that each team can access data for only the team's own customers.
Which solution will meet these requirements?

A) Create a custom service role that has Amazon S3 access. Ask teams to specify the customer name on each Amazon Bedrock request.
B) Create one Amazon Bedrock role that has full Amazon S3 access. Create IAM roles for each team that have access to only each team's customer folders.
C) Create an Amazon Bedrock custom service role for each team that has access to only the team's customer data.
D) Redact personal data in Amazon S3. Update the S3 bucket policy to allow team access to customer data.

3. A company has thousands of customer support interactions per day and wants to analyze these interactions to identify frequently asked questions and develop insights.
Which AWS service can the company use to meet this requirement?

A) Amazon Comprehend
B) Amazon Translate
C) Amazon Transcribe
D) Amazon Lex

4. A company wants to create a chatbot by using a foundation model (FM) on Amazon Bedrock. The FM needs to access encrypted data that is stored in an Amazon S3 bucket.
The data is encrypted with Amazon S3 managed keys (SSE-S3).
The FM encounters a failure when attempting to access the S3 bucket data.
Which solution will meet these requirements?

A) Ensure that the role that Amazon Bedrock assumes has permission to decrypt data with the correct encryption key.
B) Set the access permissions for the S3 buckets to allow public access to enable access over the internet.
C) Use prompt engineering techniques to tell the model to look for information in Amazon S3.
D) Ensure that the S3 data does not contain sensitive information.

5. 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) Upload PDF documents to an Amazon Bedrock knowledge base. Use the knowledge base to provide context when users submit prompts to Amazon Bedrock.
B) Use all the PDF documents to fine-tune a model with Amazon Bedrock. Use the fine-tuned model to process user prompts.
C) Use prompt engineering to add one PDF file as context to the user prompt when the prompt is submitted to Amazon Bedrock.
D) Use prompt engineering to add all the PDF files as context to the user prompt when the prompt is submitted to Amazon Bedrock.

Solutions: