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: Sep 25, 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 content moderation system needs to identify specific grammatical patterns in user-generated text, such as detecting imperative sentences (commands) or questions. The team wants to understand the grammatical structure and parts of speech (nouns, verbs, adjectives) in text before making moderation decisions.Which Amazon Comprehend feature should they use?
Answer: B
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A content moderation system needs to identify specific grammatical patterns in user-generated text, such as detecting imperative sentences (commands) or questions. The team wants to understand the grammatical structure and parts of speech (nouns, verbs, adjectives) in text before making moderation decisions.Which Amazon Comprehend feature should they use?
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Question 2
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A fintech company is launching a GenAI-powered "Spending Analyzer" feature. The application uses a Large Language Model (LLM) on Amazon Bedrock to explain transaction history to users. The project has two critical governance requirements:Compliance: The model must strictly refuse to answer any questions related to "Tax Advice" or "Legal Liability," as the company is not licensed to provide these services.Agility: The non-technical Product Team needs the ability to update the "Persona" and "Output Format" (e.g., switching from paragraphs to bullet points) of the analyzer weekly without requiring the engineering team to deploy new application code.Which combination of AWS GenAI features should the developer implement to meet these requirements? (Choose two)
Answer: B,E
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A fintech company is launching a GenAI-powered "Spending Analyzer" feature. The application uses a Large Language Model (LLM) on Amazon Bedrock to explain transaction history to users. The project has two critical governance requirements:Compliance: The model must strictly refuse to answer any questions related to "Tax Advice" or "Legal Liability," as the company is not licensed to provide these services.Agility: The non-technical Product Team needs the ability to update the "Persona" and "Output Format" (e.g., switching from paragraphs to bullet points) of the analyzer weekly without requiring the engineering team to deploy new application code.Which combination of AWS GenAI features should the developer implement to meet these requirements? (Choose two)
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Question 3
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A large financial services enterprise is building a centralized platform to allow internal development teams to consume Foundation Models (FMs) from Amazon Bedrock. To ensure strict compliance and governance, the organization requires a "GenAI Gateway" architecture.The architecture must meet the following requirements:Prevent "Shadow AI" by forcing all internal applications to route requests through a single control point that logs every prompt and response for auditing.Automate the testing of prompt templates. Whenever a prompt engineer updates a standard system prompt, it must be automatically evaluated for toxicity and accuracy before being made available to applications.Ensure that PII is automatically redacted from prompts before they are sent to the model provider.Which combination of actions should you implement to achieve this?
Answer: D,E
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A large financial services enterprise is building a centralized platform to allow internal development teams to consume Foundation Models (FMs) from Amazon Bedrock. To ensure strict compliance and governance, the organization requires a "GenAI Gateway" architecture.The architecture must meet the following requirements:Prevent "Shadow AI" by forcing all internal applications to route requests through a single control point that logs every prompt and response for auditing.Automate the testing of prompt templates. Whenever a prompt engineer updates a standard system prompt, it must be automatically evaluated for toxicity and accuracy before being made available to applications.Ensure that PII is automatically redacted from prompts before they are sent to the model provider.Which combination of actions should you implement to achieve this?
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Question 4
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A company is developing a customer support application that uses Amazon Bedrock foundation models(FMs) to provide real-time AI assistance to the company’s employees. The application must display AIgenerated responses character by character as the responses are generated. The application needs to supportthousands of concurrent users with minimal latency. The responses typically take 15 to 45 seconds to finish.Which solution will meet these requirements?
Answer: A
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A company is developing a customer support application that uses Amazon Bedrock foundation models(FMs) to provide real-time AI assistance to the company’s employees. The application must display AIgenerated responses character by character as the responses are generated. The application needs to supportthousands of concurrent users with minimal latency. The responses typically take 15 to 45 seconds to finish.Which solution will meet these requirements?
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Question 5
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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?