100% Free Amazon AIP-C01 Practice Test Questions

Question 1

A legal tech company uses Amazon Bedrock to extract specific liability clauses from uploaded contracts. Users have reported instances where the model "hallucinates" clauses that do not exist in the source text.Which mechanisms should the developer implement to verify accuracy and reduce these hallucinations?

A : Define a JSON Schema representing the expected liability data structure and include it in the model instructions to enforce constrained, deterministic output.

B : Implement a post-processing workflow that calculates the semantic similarity score between the generated response and the source text, rejecting responses that fall below a defined confidence threshold.

C : Configure Amazon Bedrock Guardrails with a "Sensitive Information" filter to redact names and addresses found in the contract clauses.

D : Increase the inference temperature parameter to 0.9 and enable Top-P sampling to broaden the diversity of the generated clauses.

E : Use Amazon CloudWatch to monitor the InvocationLatency and ModelTokenCount metrics to identify anomalies in the model's processing speed.

Answer: A,B

Question 2

A company has set up Amazon Q Developer Pro licenses for all developers at the company. The companymaintains a list of approved resources that developers must use when developing applications. The approvedresources include internal libraries, proprietary algorithmic techniques, and sample code with approvedstyling.A new team of developers is using Amazon Q Developer to develop a new Java-based application. Thecompany must ensure that the new developer team uses the company’s approved resources. The companydoes not want to make project-level modifications.Which solution will meet these requirements?

A : Create a Git repository that contains all of the approved internal libraries, algorithms, and code samples.Include this Git repository in the application project locally as part of the workspace. Ensure that thedevelopers use the workspace context to retrieve suggestions from the Git repository.

B : In the project root folder, create a folder named amazonq/rules. Add the approved internal libraries,algorithms, and code samples to the folder.

C : Create a folder in the application project named rules. Store the guidelines and code in the folder forAmazon Q Developer to reference for code suggestions.

D : Create an Amazon Q Developer customization that includes the approved data sources. Ensure that thedevelopers use the customization to develop the application.

Answer: D

Question 3

A company is designing a canary deployment strategy for a payment processing API. The system mustsupport automated gradual traffic shifting between multiple Amazon Bedrock models based on real-timeinference metrics, historical traffic patterns, and service health. The solution must be able to graduallyincrease traffic to new model versions. The system must increase traffic if metrics remain healthy anddecrease traffic if the performance degrades below acceptable thresholds.The company needs to comprehensively monitor inference latency and error rates during the deploymentphase. The company must also be able to halt deployments and revert to a previous model version without anymanual intervention.Which solution will meet these requirements?

A : Use Amazon Bedrock with provisioned throughput to host model versions. Configure an AmazonEventBridge rule to invoke an AWS Step Functions workflow when a new model version is released.Configure the workflow to shift traffic in stages, wait for a specified time period, and invoke an AWSLambda function to check Amazon CloudWatch performance metrics. Configure the workflow toincrease traffic if metrics meet thresholds and to trigger a traffic rollback if performance metrics fallbelow thresholds.

B : Use AWS Lambda functions to invoke various Amazon Bedrock model versions. Use an Amazon APIGateway HTTP API with stage variables and weighted routing to shift traffic gradually. Use AmazonCloudWatch to monitor performance. Use external logic to adjust traffic and roll back if performancefalls below thresholds.

C : Use Amazon SageMaker AI endpoint variants to represent multiple Amazon Bedrock model versions.Use variant weights to shift traffic. Use Amazon CloudWatch and SageMaker Model Monitor to triggerrollbacks. Use EventBridge to roll back deployments if an anomaly is detected.

D : Use Amazon OpenSearch Service to track inference logs. Configure OpenSearch Service to invoke anAWS Systems Manager Automation runbook to update Amazon Bedrock model endpoints to shifttraffic based on inference logs.

Answer: A

Question 4

A company is building an AI advisory application by using Amazon Bedrock. The application will providerecommendations to customers. The company needs the application to explain its reasoning process and citespecific sources for data. The application must retrieve information from company data sources and show stepby-step reasoning for recommendations. The application must also link data claims to source documents andmaintain response latency under 3 seconds.Which solution will meet these requirements with the LEAST operational overhead?

A : Use Amazon Bedrock Knowledge Bases with source attribution enabled. Use the Anthropic ClaudeMessages API with RAG to set high-relevance thresholds for source documents. Store reasoning andcitations in Amazon S3 for auditing purposes.

B : Use Amazon Bedrock with Anthropic Claude models and extended thinking. Configure a 4,000-tokenthinking budget. Store reasoning traces and citations in Amazon DynamoDB for auditing purposes.

C : Configure Amazon SageMaker AI with a custom Anthropic Claude model. Use the model’s reasoningparameter and AWS Lambda to process responses. Add source citations from a separate Amazon RDSdatabase.

D : Use Amazon Bedrock with Anthropic Claude models and chain-of-thought reasoning. Configurecustom retrieval tracking with the Amazon Bedrock Knowledge Bases API. Use Amazon CloudWatchto monitor response latency metrics.

Answer: A

Question 5

A company is creating a workflow to review customer-facing communications before the company sends thecommunications. The company uses a pre-defined message template to generate the communications andstores the communications in an Amazon S3 bucket. The workflow needs to capture a specific portion fromthe template and send it to an Amazon Bedrock model. The workflow must store model responses back to theoriginal S3 bucket.Which solution will meet these requirements?

A : Create a flow in Amazon Bedrock Flows. Configure S3 action nodes at the beginning and end of theflow to retrieve and store the communications and the model responses. In the middle of the flow,configure an expression to parse each communication. Configure an agent step to send the parsed inputto the model for review.

B : Create an AWS Step Functions Express workflow state machine. Use an Amazon S3 integrationGetObject step to retrieve the original communications. Use an intrinsic function Pass step to parse thecommunications and to pass the results to an Amazon Bedrock InvokeModel step. Configure anAmazon S3 integration PutObject step to store the model responses back to the S3 bucket.

C : Create an Amazon Bedrock agent that has an action group. Configure instructions to define how theagent should parse the communications. Configure the action group to retrieve the communicationsfrom the S3 bucket, invoke the Amazon Bedrock model, and store the model responses back to the S3bucket.

D : Create an Amazon Bedrock agent that has a single action group. Configure three AWS Lambdafunctions in the action group. Configure the functions to retrieve the communications from the S3bucket, parse the communications and invoke the Amazon Bedrock model, and store the modelresponses back to the S3 bucket.

Answer: A

100% Free AIP-C01 Practice Exam Questions and Answers