Free Amazon AIP-C01 Exam Questions
Absolute Free AIP-C01 Exam Practice for Comprehensive Preparation
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Amazon AIP-C01 Exam Questions
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Provided By: Amazon
- Exam: AWS Certified Generative AI Developer - Professional
- Certification: AWS Certified Professional
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Total Questions: 380
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Updated On: Apr 22, 2026
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Rated: 4.9 |
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Online Users: 760
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Question 1
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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?
Answer: A,B
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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?
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Question 2
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An online gaming platform is launching a GenAI-powered support assistant using multiple Foundation Models (FMs) available in Amazon Bedrock (including Amazon Titan and Anthropic Claude). The security team has issued strict requirements for the assistant's input handling:PII Protection: Users must be prevented from submitting email addresses or phone numbers.Toxicity: Hate speech and insults must be blocked immediately.Custom Blocking: A specific list of known "cheat codes" and "exploit keywords" must be blocked from entering the model context.Consistency: These rules must apply uniformly across all used FMs without rewriting application logic for each model.Which solution should you implement to meet these requirements with the LEAST operational overhead?
Answer: D
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An online gaming platform is launching a GenAI-powered support assistant using multiple Foundation Models (FMs) available in Amazon Bedrock (including Amazon Titan and Anthropic Claude). The security team has issued strict requirements for the assistant's input handling:PII Protection: Users must be prevented from submitting email addresses or phone numbers.Toxicity: Hate speech and insults must be blocked immediately.Custom Blocking: A specific list of known "cheat codes" and "exploit keywords" must be blocked from entering the model context.Consistency: These rules must apply uniformly across all used FMs without rewriting application logic for each model.Which solution should you implement to meet these requirements with the LEAST operational overhead?
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Question 3
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A company has a centralized AI team managing Bedrock models in Account A. Three development teams in Accounts B, C, and D need access to a specific Claude Sonnet model with provisioned throughput for their applications. The solution must ensure that these accounts can ONLY invoke this specific model and cannot access any other Bedrock models or features in Account A. The solution must also allow the central AI team to monitor usage and apply guardrails centrally without requiring changes in the development accounts.Which solution meets ALL these requirements?
Answer: D
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A company has a centralized AI team managing Bedrock models in Account A. Three development teams in Accounts B, C, and D need access to a specific Claude Sonnet model with provisioned throughput for their applications. The solution must ensure that these accounts can ONLY invoke this specific model and cannot access any other Bedrock models or features in Account A. The solution must also allow the central AI team to monitor usage and apply guardrails centrally without requiring changes in the development accounts.Which solution meets ALL these requirements?
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Question 4
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A financial services firm processes thousands of unstructured PDF earnings reports daily. The engineering team uses Anthropic Claude 4.5 Sonnet on Amazon Bedrock to extract specific Key Performance Indicators (KPIs) and populate a downstream SQL database.Users have reported that while the model handles narrative text well, it consistently hallucinates values when processing financial tables that span multiple pages or contain complex nested headers. The raw text ingested from the OCR pipeline often arrives with broken formatting, missing whitespace, and merged columns.Which strategy should the GenAI Developer implement to enhance the input data quality and resolve the extraction errors?
Answer: C
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A financial services firm processes thousands of unstructured PDF earnings reports daily. The engineering team uses Anthropic Claude 4.5 Sonnet on Amazon Bedrock to extract specific Key Performance Indicators (KPIs) and populate a downstream SQL database.Users have reported that while the model handles narrative text well, it consistently hallucinates values when processing financial tables that span multiple pages or contain complex nested headers. The raw text ingested from the OCR pipeline often arrives with broken formatting, missing whitespace, and merged columns.Which strategy should the GenAI Developer implement to enhance the input data quality and resolve the extraction errors?
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Question 5
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A company is building a multicloud generative AI (GenAI)-powered secret resolution application that usesAmazon Bedrock and Agent Squad. The application resolves secrets from multiple sources, including keystores and hardware security modules (HSMs). The application uses AWS Lambda functions to retrievesecrets from the sources. The application uses AWS AppConfig to implement dynamic feature gating. Theapplication supports secret chaining and detects secret drift. The application handles short-lived and expiringsecrets. The application also supports prompt flows for templated instructions. The application uses AWSStep Functions to orchestrate agents to resolve the secrets and to manage secret validation and drift detection.The company finds multiple issues during application testing. The application does not refresh expired secretsin time for agents to use. The application sends alerts for secret drift, but agents still use stale data. Promptflows within the application reuse outdated templates, which cause cascading failures. The company mustresolve the performance issues.Which solution will meet this requirement?
Answer: A
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A company is building a multicloud generative AI (GenAI)-powered secret resolution application that usesAmazon Bedrock and Agent Squad. The application resolves secrets from multiple sources, including keystores and hardware security modules (HSMs). The application uses AWS Lambda functions to retrievesecrets from the sources. The application uses AWS AppConfig to implement dynamic feature gating. Theapplication supports secret chaining and detects secret drift. The application handles short-lived and expiringsecrets. The application also supports prompt flows for templated instructions. The application uses AWSStep Functions to orchestrate agents to resolve the secrets and to manage secret validation and drift detection.The company finds multiple issues during application testing. The application does not refresh expired secretsin time for agents to use. The application sends alerts for secret drift, but agents still use stale data. Promptflows within the application reuse outdated templates, which cause cascading failures. The company mustresolve the performance issues.Which solution will meet this requirement?