AIP-C01 Amazon-Web-Services Exam Questions and Free Practice Test

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AIP-C01 Exam

Question 7

A bank is developing a generative AI (GenAI)-powered AI assistant that uses Amazon Bedrock to assist the bank??s website users with account inquiries and financial guidance. The bank must ensure that the AI assistant does not reveal any personally identifiable information (PII) in customer interactions.
The AI assistant must not send PII in prompts to the GenAI model. The AI assistant must not respond to customer requests to provide investment advice. The bank must collect audit logs of all customer interactions, including any images or documents that are transmitted during customer interactions.
Which solution will meet these requirements with the LEAST operational effort?

A. Use Amazon Macie to detect and redact PII in user inputs and in the model response

B. Apply prompt engineering techniques to force the model to avoid investment advice topic

C. Use AWS CloudTrail to capture conversation logs.

D. Use an AWS Lambda function and Amazon Comprehend to detect and redact PI

E. Use Amazon Comprehend topic modeling to prevent the AI assistant from discussing investment advice topic

F. Set up custom metrics in Amazon CloudWatch to capture customer conversations.

G. Configure Amazon Bedrock guardrails to apply a sensitive information policy to detect and filter PI

H. Set up a topic policy to ensure that the AI assistant avoids investment advice topic

I. Use the Converse API to log model invocation

J. Enable delivery and image logging to Amazon S3.

K. Use regex controls to match patterns for PI

L. Apply prompt engineering techniques to avoid returning PII or investment advice topics to customer

M. Enable model invocation logging, delivery logging, and image logging to Amazon S3.

Correct Answer:C

Question 8

A medical company is creating a generative AI (GenAI) system by using Amazon Bedrock. The system processes data from various sources and must maintain end-to-end data lineage. The system must also use real-time personally identifiable information (PII) filtering and audit trails to automatically report compliance.
Which solution will meet these requirements?

A. Use AWS Glue Data Catalog to register all data sources and track lineag

B. Use Amazon Bedrock Guardrails PII filter

C. Enable AWS CloudTrail logging for all Amazon Bedrock API calls with Amazon S3 integratio

D. Use Amazon Macie to scan stored data for sensitive information and publish findings to Amazon CloudWatch Log

E. Create CloudWatch dashboards to visualize the findings and generate automated compliance reports.

F. Use AWS Config to track data source configurations and change

G. Use AWS WAF with custom rules to filter PII at the application layer before Amazon Bedrock processes the dat

H. Configure Amazon EventBridge to capture and route audit events to Amazon S3. Use Amazon Comprehend Medical with scheduled AWS Lambda functions to analyze stored outputs for compliance violations.

I. Use AWS DataSync to replicate data sources to track lineag

J. Configure Amazon Macie to scan Amazon Bedrock outputs for sensitive informatio

K. Use AWS Systems Manager Session Manager to log user interaction

L. Deploy Amazon Textract with AWS Step Functions workflows to identify and redact PII from generated reports.

M. Configure Amazon Athena to query data sources to analyze and report on data lineag

N. Use Amazon CloudWatch custom metrics to monitor PII exposure in Amazon Bedrock responses and establish AWS X-Ray tracing to generate an audit trai

O. Use an Amazon Rekognition Custom Labels model to detect sensitive information in the data that Amazon Bedrock processes.

Correct Answer:A

Question 9

A wildlife conservation agency operates zoos globally. The agency uses various sensors, trackers, and audiovisual recorders to monitor animal behavior. The agency wants to launch a generative AI (GenAI) assistant that can ingest multimodal data to study animal behavior.
The GenAI assistant must support natural language queries, avoid speculative behavioral interpretations, and maintain audit logs for ethical research audits.
Which solution will meet these requirements?

A. Ingest raw videos into Amazon Rekognition to detect animal postures and expression

B. Use Amazon Data Firehose to stream sensor and GPS data into Amazon S3. Prompt an Amazon Bedrock FM using basic templates stored in AWS Systems Manager Parameter Stor

C. Use IAM for access contro

D. Use AWS CloudTrail for audit logging.

E. Use Amazon SageMaker Processing and Amazon Transcribe to pre-process multimodal dat

F. Ingest curated summaries into an Amazon Bedrock Knowledge Base

G. Apply Amazon Bedrock guardrails to restrict speculative output

H. Use AWS AppConfig to manage prompt template

I. Use AWS CloudTrail to log research activity for audits.

J. Use Amazon OpenSearch Serverless to index behavioral logs and telemetr

K. Use Amazon Comprehend to extract entitie

L. Use Amazon Bedrock to answer questions over indexed dat

M. Use IAM for access control and CloudTrail for audit logging.

N. Configure Amazon O Business to federate data across Amazon S3, Amazon Kinesis, and Amazon SageMaker Feature Stor

O. Use EventBridge for ingestion orchestratio

P. Use custom AWS Lambda functions to filter LLM outputs for ethical compliance.

Correct Answer:B

Question 10

An insurance company uses existing Amazon SageMaker AI infrastructure to support a web-based application that allows customers to predict what their insurance premiums will be. The company stores customer data that is used to train the SageMaker AI model in an Amazon S3 bucket. The dataset is growing rapidly. The company wants a solution to continuously re-train the model. The solution must automatically re-train and re-deploy the model to the application when an employee uploads a new customer data file to the S3 bucket.
Which solution will meet these requirements?

A. Use AWS Glue to run an ETL job on each uploaded fil

B. Configure the ETL job to use the AWS SDK to invoke the SageMaker AI model endpoin

C. Use real-time inference with the endpoint to re-deploy the model after it is re-trained on the updated customer dataset.

D. Create an AWS Lambda function and webhook handlers to generate an event when an employee uploads a new fil

E. Configure SageMaker Pipelines to re-deploy the model after it is re-trained on the updated customer datase

F. Use Amazon EventBridge to create an event bu

G. Set the Lambda function event as the source and SageMaker Pipelines as the target.

H. Create an AWS Step Functions Express workflow with AWS SDK integrations to retrieve the customer data from the S3 bucket when an employee uploads a new file to the S3 bucke

I. Use a SageMaker Data Wrangler flow to export the data from the S3 bucket to SageMaker Autopilo

J. Use the SageMaker Autopilot to re-deploy the model after it has been re-trained on the updated customer dataset.

K. Create an AWS Step Functions Standard workflo

L. Configure the first state to call an AWS Lambda function to respond when an employee uploads a new file to the S3 bucke

M. Use a pipeline in SageMaker Pipelines to re-deploy the model after it has been re-trained on the updated customer datase

N. Use the next state in the workflow to run the pipeline when the first state receives a response.

Correct Answer:D

Question 11

An ecommerce company operates a global product recommendation system that needs to switch between multiple foundation models (FMs) in Amazon Bedrock based on regulations, cost optimization, and performance requirements. The company must apply custom controls based on proprietary business logic, including dynamic cost thresholds, AWS Region-specific compliance rules, and real-time A/B testing across multiple FMs. The system must be able to switch between FMs without deploying new code. The system must route user requests based on complex rules including user tier, transaction value, regulatory zone, and real-time cost metrics that change hourly and require immediate propagation across thousands of concurrent requests.
Which solution will meet these requirements?

A. Deploy an AWS Lambda function that uses environment variables to store routing rules and Amazon Bedrock FM ID

B. Use the Lambda console to update the environment variables when business requirements chang

C. Configure an Amazon API Gateway REST API to read request parameters to make routing decisions.

D. Deploy Amazon API Gateway REST API request transformation templates to implement routing logic based on request attribute

E. Store Amazon Bedrock FM endpoints as REST API stage variable

F. Update the variables when the system switches between models.

G. Configure an AWS Lambda function to fetch routing configuration from the AWS AppConfig Agent for each user reques

H. Run business logic in the Lambda function to select the appropriate FM for each reques

I. Expose the FM through a single Amazon API Gateway REST API endpoint.

J. Use AWS Lambda authorizers for an Amazon API Gateway REST API to evaluate routing rules that are stored in AWS AppConfi

K. Return authorization contexts based on business logi

L. Route requests to model-specific Lambda functions for each Amazon Bedrock FM.

Correct Answer:C

Question 12

A company developed a multimodal content analysis application by using Amazon Bedrock. The application routes different content types (text, images, and code) to specialized foundation models (FMs).
The application needs to handle multiple types of routing decisions. Simple routing based on file extension must have minimal latency. Complex routing based on content semantics requires analysis before FM selection. The application must provide detailed history and support fallback options when primary FMs fail.
Which solution will meet these requirements?

A. Configure AWS Lambda functions that call Amazon Bedrock FMs for all routing logi

B. Use conditional statements to determine the appropriate FM based on content type and semantics.

C. Create a hybrid solutio

D. Handle simple routing based on file extensions in application cod

E. Handle complex content-based routing by using an AWS Step Functions state machine with JSONata for content analysis and the InvokeModel API for specialized FMs.

F. Deploy separate AWS Step Functions workflows for each content type with routing logic in AWS Lambda function

G. Use Amazon EventBridge to coordinate between workflows when fallback to alternate FMs is required.

H. Use Amazon SQS with different SQS queues for each content typ

I. Configure AWS Lambda consumers that analyze content and invoke appropriate FMs based on message attributes by using Amazon Bedrock with an AWS SDK.

Correct Answer:B

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