Question 1
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.
CORRECT ANSWER
A. Ensure that the role that Amazon Bedrock assumes has permission to decrypt data
with the correct encryption key.
Question 2
A company wants to use language models to create an application for inference on edge
devices. The inference must have the lowest latency possible.Which solution will meet
these requirements?
A. Deploy optimized small language models (SLMs) on edge devices.
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,B. Deploy optimized large language models (LLMs) on edge devices.
C. Incorporate a centralized small language model (SLM) API for asynchronous
communication with edge devices.
D. Incorporate a centralized large language model (LLM) API for asynchronous
communication with edge devices.
CORRECT ANSWER
A. Deploy optimized small language models (SLMs) on edge devices.
Question 3
A company wants to use generative AI to increase developer productivity and software
development. The company wants to use Amazon Q Developer.What can Amazon Q
Developer do to help the company meet these requirements?
A. Create software snippets, reference tracking, and open source license tracking.
B. Run an application without provisioning or managing servers.
C. Enable voice commands for coding and providing natural language search.
D. Convert audio files to text documents by using ML models.
CORRECT ANSWER
A. Create software snippets, reference tracking, and open source license tracking.
Question 4
A company wants to build an ML model by using Amazon SageMaker. The company needs
to share and manage variables for model development across multiple teams.Which
SageMaker feature meets these requirements?
A. Amazon SageMaker Feature Store
B. Amazon SageMaker Data Wrangler
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, C. Amazon SageMaker Clarify
D. Amazon SageMaker Model Cards
CORRECT ANSWER
A. Amazon SageMaker Feature Store
Question 5
A company is using a pre-trained large language model (LLM) to build a chatbot for
product recommendations. The company needs the LLM outputs to be short and written
in a specific language.Which solution will align the LLM response quality with the
company's expectations?
A. Adjust the prompt.
B. Choose an LLM of a different size.
C. Increase the temperature.
D. Increase the Top K value.
CORRECT ANSWER
A. Adjust the prompt.
Question 6
A company uses Amazon SageMaker for its ML pipeline in a production environment. The
company has large input data sizes up to 1 GB and processing times up to 1 hour. The
company needs near real-time latency.Which SageMaker inference option meets these
requirements?
A. Real-time inference
B. Serverless inference
C. Asynchronous inference
3
@THE STUDY VAULT
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.
CORRECT ANSWER
A. Ensure that the role that Amazon Bedrock assumes has permission to decrypt data
with the correct encryption key.
Question 2
A company wants to use language models to create an application for inference on edge
devices. The inference must have the lowest latency possible.Which solution will meet
these requirements?
A. Deploy optimized small language models (SLMs) on edge devices.
1
@THE STUDY VAULT
,B. Deploy optimized large language models (LLMs) on edge devices.
C. Incorporate a centralized small language model (SLM) API for asynchronous
communication with edge devices.
D. Incorporate a centralized large language model (LLM) API for asynchronous
communication with edge devices.
CORRECT ANSWER
A. Deploy optimized small language models (SLMs) on edge devices.
Question 3
A company wants to use generative AI to increase developer productivity and software
development. The company wants to use Amazon Q Developer.What can Amazon Q
Developer do to help the company meet these requirements?
A. Create software snippets, reference tracking, and open source license tracking.
B. Run an application without provisioning or managing servers.
C. Enable voice commands for coding and providing natural language search.
D. Convert audio files to text documents by using ML models.
CORRECT ANSWER
A. Create software snippets, reference tracking, and open source license tracking.
Question 4
A company wants to build an ML model by using Amazon SageMaker. The company needs
to share and manage variables for model development across multiple teams.Which
SageMaker feature meets these requirements?
A. Amazon SageMaker Feature Store
B. Amazon SageMaker Data Wrangler
2
@THE STUDY VAULT
, C. Amazon SageMaker Clarify
D. Amazon SageMaker Model Cards
CORRECT ANSWER
A. Amazon SageMaker Feature Store
Question 5
A company is using a pre-trained large language model (LLM) to build a chatbot for
product recommendations. The company needs the LLM outputs to be short and written
in a specific language.Which solution will align the LLM response quality with the
company's expectations?
A. Adjust the prompt.
B. Choose an LLM of a different size.
C. Increase the temperature.
D. Increase the Top K value.
CORRECT ANSWER
A. Adjust the prompt.
Question 6
A company uses Amazon SageMaker for its ML pipeline in a production environment. The
company has large input data sizes up to 1 GB and processing times up to 1 hour. The
company needs near real-time latency.Which SageMaker inference option meets these
requirements?
A. Real-time inference
B. Serverless inference
C. Asynchronous inference
3
@THE STUDY VAULT
