AIP-C01 Exam Simulation — 200 Questions

Question 1

Which TWO steps are required to properly secure Bedrock Knowledge Bases?

Accepted Answer

Use IAM roles for the Knowledge Base to access data. Enabling encryption and managing IAM access are the primary security configurations.

Answer

Disable all encryption to increase performance

Answer

Place the Knowledge Base in a public subnet

Answer

Grant public read access to the S3 bucket

Question 2

Which AWS service is used to monitor and log the prompts sent to an Amazon Bedrock model for auditing purposes?

Accepted Answer

AWS CloudTrail. AWS CloudTrail logs all API calls made to Amazon Bedrock, providing the necessary audit trail for prompt usage.

Answer

AWS Config

Answer

Amazon Macie

Answer

Amazon CloudWatch Logs

Question 3

What is the role of an AWS Service Control Policy (SCP) in an AI governance framework?

Accepted Answer

To enforce organizational compliance and restrict service access. SCPs provide centralized guardrails to define the maximum permissions that can be granted to IAM roles across all accounts in an organization.

Answer

To store model weights securely

Answer

To automatically optimize model latency

Answer

To monitor user chat history

Question 4

You are designing a secure Generative AI architecture on AWS. Which TWO of the following are recommended practices for securing the data ingestion pipeline for RAG?

Accepted Answer

Enforce TLS 1.2+ for all data movement. Encrypting data in transit (TLS) and at rest (KMS) are fundamental for data pipeline security.

Answer

Disable all logging in the pipeline to prevent data exposure

Answer

Store API keys in plain text within the Lambda code

Answer

Store all documents in a public S3 bucket for ease of access

Question 5

When using the Amazon Bedrock Converse API, which parameter enables the model to perform tool use by providing a definition of available functions?

Accepted Answer

toolConfig. The tools parameter in the Converse API allows you to define a list of tools for the model to use.

Answer

inferenceConfig

Answer

system

Answer

additionalModelRequestFields

Question 6

When troubleshooting a SageMaker endpoint that consistently returns 503 Service Unavailable errors, which THREE areas should you investigate?

Accepted Answer

Instance memory usage. 503s typically point to capacity limits, health check failures, or resource exhaustion (memory/GPU).

Answer

IAM role permissions

Answer

Input JSON schema validation

Question 7

Which AWS tool is used to monitor the performance and latency of an application calling Bedrock?

Accepted Answer

Amazon CloudWatch. Amazon CloudWatch provides metrics for request latency, invocation count, and errors for Bedrock models.

Answer

Amazon Inspector

Answer

AWS CloudTrail

Answer

AWS Config

Question 8

An organization wants to use a model that supports both text and image input. Which family of foundation models should they select in Amazon Bedrock?

Accepted Answer

Claude 3 Sonnet. Amazon Bedrock supports multi-modal models like Claude 3 Sonnet and Claude 3 Opus which handle both text and images.

Answer

Amazon Titan Text Express

Answer

Jurassic-2 Mid

Answer

Cohere Command R

Question 9

A developer is optimizing a RAG solution for a legal firm. The documents are highly dense and technical. Which chunking strategy in Amazon Bedrock Knowledge Bases provides the best balance of retrieval accuracy?

Accepted Answer

Hierarchical chunking.. Hierarchical chunking is designed for complex documents by creating parent and child chunks, which helps maintain context during retrieval.

Answer

Semantic chunking based on paragraph breaks.

Answer

Fixed-size chunking with 100 token overlap.

Answer

Default chunking strategy.

Question 10

A developer wants to choose a foundation model in Amazon Bedrock that offers the best balance of reasoning capability and latency for a customer support chatbot. Which tool should the developer use to evaluate models?

Accepted Answer

Bedrock Model Evaluation jobs.. The Bedrock Model Evaluation service allows developers to compare model performance using automated and human-in-the-loop metrics.

Answer

Amazon CloudWatch Metrics for Bedrock.

Answer

AWS Glue DataBrew.

Answer

Amazon SageMaker Model Monitor.

Question 11

A developer needs to integrate a foundation model that requires custom fine-tuning for a specific domain language. Which service provides the environment for this task?

Accepted Answer

Amazon Bedrock Custom Models. Amazon Bedrock Custom Models allow for fine-tuning base models on private datasets to improve performance on specific tasks or domains.

Answer

AWS Glue DataBrew

Answer

Amazon SageMaker JumpStart

Answer

Amazon Kendra

Question 12

A developer needs to measure the quality of a RAG application's responses. Which tool within Amazon Bedrock facilitates this?

Accepted Answer

Amazon Bedrock Model Evaluation.. Amazon Bedrock Model Evaluation allows users to evaluate their models or RAG pipelines against custom or built-in datasets.

Answer

Amazon CloudWatch Metrics.

Answer

AWS Glue Quality Rules.

Answer

Amazon SageMaker Model Monitor.

Question 13

Which TWO factors are critical when choosing a model for a RAG architecture that requires high grounding accuracy?

Accepted Answer

The model's support for citation and source attribution.. Accuracy in RAG relies on model reasoning capability and the quality of the retrieved chunks.

Answer

The model's training date.

Answer

The model's ability to generate images.

Answer

The number of parameters in the model.

Question 14

A firm needs to ensure that all Generative AI model training data, if used for fine-tuning, is compliant with GDPR. Where should the training data reside?

Accepted Answer

Region-compliant S3 buckets with restricted IAM access and encryption. The data should be stored in S3 buckets located within the region that complies with GDPR, with appropriate encryption and access controls.

Answer

Publicly accessible S3 buckets

Answer

Temporary local storage on the training instance

Answer

DynamoDB tables

Question 15

Which Amazon Bedrock feature allows developers to restrict user queries based on specific topics or harmful content categories?

Accepted Answer

Amazon Bedrock Guardrails. Amazon Bedrock Guardrails provide a structured way to define policies that filter input and output based on topics, PII, and harmful content.

Answer

Knowledge Base Vector Index policies

Answer

Cross-region inference

Answer

Model Invocation Logs

Question 16

A company is concerned about model provider policy compliance. Where can they find the specific data processing terms for their chosen model?

Accepted Answer

In the AWS Service Terms and individual model provider documentation.. The AWS Service Terms and the Bedrock documentation page specify the data handling and privacy commitments for each model provider.

Answer

In the Amazon Bedrock console 'Model Evaluation' tab.

Answer

By asking the model during an inference session.

Answer

In the Amazon CloudWatch monitoring dashboard.

Question 17

When designing a RAG system, why would a developer choose Amazon Titan Text Embeddings over a third-party embedding model?

Accepted Answer

It is optimized for Amazon Bedrock Knowledge Bases, ensuring seamless integration and scalability.. Amazon Titan Embeddings are optimized to work natively with Amazon Bedrock Knowledge Bases and provide high performance and integration benefits.

Answer

It supports multi-modal input processing natively.

Answer

It is the only model that supports English.

Answer

It prevents the model from hallucinating.

Question 18

Which metric should a developer monitor to ensure the RAG system remains performant as usage increases?

Accepted Answer

Inference Latency.. Latency and Token Consumption (or request count) are key indicators of RAG performance and cost efficiency.

Answer

Vector Database Storage Capacity.

Answer

IAM User Count.

Answer

Model Training Loss.

Question 19

You are deploying a model from SageMaker JumpStart. You need to ensure that the model inference container has access to private VPC resources. What must you configure?

Accepted Answer

Configure Subnets and Security Groups in the Model creation. You must configure the VPC settings (Subnets and Security Groups) in the SageMaker Model configuration to allow network access.

Answer

Set the IAM role to 'AdministratorAccess'

Answer

Update the JumpStart model Dockerfile

Answer

Enable AWS PrivateLink on the S3 bucket

Question 20

Which configuration in an Amazon Bedrock Knowledge Base is essential for updating the vector index whenever the source files in S3 change?

Accepted Answer

Configure Data Source Syncing.. Syncing is triggered via the 'Sync' operation, but for automation, S3 Event Notifications coupled with a Lambda function or the Bedrock Sync API is required.

Answer

Use AWS Config to monitor bucket changes.

Answer

Set the knowledge base to 'Auto-Refresh' mode.

Answer

Enable S3 Versioning.