AIP-C01 Practice Test 5 — 10 Questions

Question 1

When preparing data for a Knowledge Base, why is it recommended to remove PII?

Accepted Answer

To comply with data privacy policies and reduce risk.. Removing PII ensures that the vector index does not store sensitive information, minimizing the risk of data leakage.

Answer

To improve model inference speed.

Answer

Because the models cannot process numbers.

Answer

To reduce the file size.

Question 2

A developer is evaluating model performance for a specific task. Which THREE metrics are commonly used in the Bedrock Model Evaluation console?

Accepted Answer

Inference latency (time to first token).. Accuracy, latency, and toxicity are standard metrics provided in model evaluation frameworks.

Answer

S3 bucket storage size.

Answer

Number of active IAM roles.

Question 3

A company requires their AI to be available even if a regional outage occurs. How do they handle Bedrock model availability?

Accepted Answer

Implement application-level logic to switch regions for inference.. Cross-region inference is not supported by all models, so the application logic must handle failover between regions where the model is available.

Answer

Use an S3 bucket in every region.

Answer

Request a cross-region Bedrock endpoint from AWS Support.

Answer

Enable global AWS region auto-scaling.

Question 4

Which TWO of the following are valid ways to improve the relevance of retrieved documents in a RAG system?

Accepted Answer

Implement metadata filtering to narrow the search space.. Metadata filtering and choosing an optimal chunking strategy are key levers to improve retrieval accuracy.

Answer

Use a larger, more generic embedding model.

Answer

Increase the number of retrieved chunks to 1000.

Answer

Delete all indices and recreate them every hour.

Question 5

Which component in Amazon Bedrock is used to define the structure of the retrieved documents before they are fed into the model?

Accepted Answer

Chunking Strategy.. The 'Chunking Strategy' determines how documents are broken down and structured before being embedded and indexed.

Answer

Prompt Template.

Answer

Vector Database index settings.

Answer

IAM Policy.

Question 6

A developer is building a RAG system and wants to include document metadata in the search retrieval. How is this done?

Accepted Answer

By adding metadata files alongside the documents in S3 and using custom ingestion logic.. Metadata is attached to the chunks in the vector index. During query, the system can use the `filter` parameter to limit results.

Answer

By prepending the metadata to the prompt.

Answer

It is done automatically by the model.

Answer

It is not possible to use metadata in Bedrock RAG.

Question 7

A developer is configuring a RAG system and wants to ensure the model has access to the most recent data. How should they handle updates?

Accepted Answer

Perform a 'Sync' operation on the Knowledge Base.. The 'Sync' operation in Knowledge Bases should be triggered whenever the source data changes in S3 to update the index.

Answer

Wait for the Bedrock service to automatically detect changes.

Answer

Use a cron job to restart the inference engine.

Answer

Delete and recreate the knowledge base daily.

Question 8

Which of the following is NOT a benefit of using Amazon Bedrock?

Accepted Answer

Full control over the model's source code.. Bedrock is a managed service, so it does not require managing the infrastructure of the underlying foundation models.

Answer

Serverless architecture.

Answer

Access to multiple FM providers via a single API.

Answer

Data privacy and security controls.

Question 9

Which TWO of the following are supported as source data for Amazon Bedrock Knowledge Bases?

Accepted Answer

Atlassian Confluence.. S3 is the primary supported source, and Confluence is also natively supported as a data source.

Answer

Email server logs.

Answer

Social media live streams.

Answer

Local hard drive files.

Question 10

What is the primary benefit of using a 'System Prompt' in Bedrock?

Accepted Answer

To provide instructions that guide the model's behavior.. The system prompt sets the behavior and constraints for the model, ensuring consistent and safe interactions.

Answer

To bypass authentication.

Answer

To increase the model's speed.

Answer

To compress the input tokens.