Amazon AIF-C01 Online Practice Questions and Exam Preparation

Amazon AIF-C01 Online Questions & Answers

• Question 211:

  HOTSPOT

  A company is using a generative AI model to develop a digital assistant. The model's responses occasionally include undesirable and potentially harmful content.

  Select the correct Amazon Bedrock filter policy from the following list for each mitigation action. Each filter policy should be selected one time. (Select FOUR.)

  

  

  Explanation:

  Block input prompts or model responses that contain harmful content such as hate, insults, violence, or misconduct - Content filters Avoid subjects related to illegal investment advice or legal advice - Denied topics Detect and block specific offensive terms - Word filters Detect and filter out information in the model's responses that is not grounded in the provided source information - Contextual grounding check

• Question 212:

  A company built an AI chatbot. The chatbot uses large language models (LLMs) to answer user questions. The company wants to keep the chatbot's LLM instructions private.

  Which security risk should the company consider?

  A. Data poisoning
  B. Prompt leakage
  C. LLM hallucinations
  D. Output ungroundedness
  B. Prompt leakage

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  Explanation

  Prompt leakage is the risk that hidden system instructions or private prompts can be exposed to users, which could reveal the chatbot's confidential LLM instructions.

• Question 213:

  A large retailer receives thousands of customer support inquiries about products every day. The customer support inquiries need to be processed and responded to quickly. The company wants to implement Agents for Amazon Bedrock. What are the key benefits of using Amazon Bedrock agents that could help this retailer?

  A. Generation of custom foundation models (FMs) to predict customer needs
  B. Automation of repetitive tasks and orchestration of complex workflows
  C. Automatically calling multiple foundation models (FMs) and consolidating the results
  D. Selecting the foundation model (FM) based on predefined criteria and metrics
  B. Automation of repetitive tasks and orchestration of complex workflows

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  Amazon Bedrock Agents provide the capability to automate repetitive tasks and orchestrate complex workflows using generative AI models. This is particularly beneficial for customer support inquiries, where quick and efficient processing is crucial.

  Option B (Correct): "Automation of repetitive tasks and orchestration of complex workflows":This is the correct answer because Bedrock Agents can automate common customer service tasks and streamline complex processes, improving response times and efficiency.

  Option A:"Generation of custom foundation models (FMs) to predict customer needs" is incorrect as Bedrock agents do not create custom models.

  Option C:"Automatically calling multiple foundation models (FMs) and consolidating the results" is incorrect because Bedrock agents focus on task automation rather than combining model outputs.

  Option D:"Selecting the foundation model (FM) based on predefined criteria and metrics" is incorrect as Bedrock agents are not designed for selecting models.

  References:

  Amazon Bedrock Documentation:AWS explains that Bedrock Agents automate tasks and manage complex workflows, making them ideal for customer support automation.

• Question 214:

  A company has built an image classification model to predict plant diseases from photos of plant leaves. The company wants to evaluate how many images the model classified correctly. Which evaluation metric should the company use to measure the model's performance?

  A. R-squared score
  B. Accuracy
  C. Root mean squared error (RMSE)
  D. Learning rate
  B. Accuracy

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  Accuracy is the most appropriate metric to measure the performance of an image classification model. It indicates the percentage of correctly classified images out of the total number of images. In the context of classifying plant diseases from images, accuracy will help the company determine how well the model is performing by showing how many images were correctly classified.

  Option B (Correct): "Accuracy":This is the correct answer because accuracy measures the proportion of correct predictions made by the model, which is suitable for evaluating the performance of a classification model.

  Option A:"R-squared score" is incorrect as it is used for regression analysis, not classification tasks.

  Option C:"Root mean squared error (RMSE)" is incorrect because it is also used for regression tasks to measure prediction errors, not for classification accuracy.

  Option D:"Learning rate" is incorrect as it is a hyperparameter for training, not a performance metric.

  References:

  Evaluating Machine Learning Models on AWS:AWS documentation emphasizes the use of appropriate metrics, like accuracy, for classification tasks.

• Question 215:

  Which AWS service or feature can help an AI development team quickly deploy and consume a foundation model (FM) within the team's VPC?

  A. Amazon Personalize
  B. Amazon SageMaker JumpStart
  C. PartyRock, an Amazon Bedrock Playground
  D. Amazon SageMaker endpoints
  B. Amazon SageMaker JumpStart

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  Amazon SageMaker JumpStart is the correct service for quickly deploying and consuming a foundation model (FM) within a team's VPC.

• Question 216:

  A software company builds tools for customers. The company wants to use AI to increase software development productivity. Which solution will meet these requirements?

  A. Use a binary classification model to generate code reviews.
  B. Install code recommendation software in the company's developer tools.
  C. Install a code forecasting tool to predict potential code issues.
  D. Use a natural language processing (NLP) tool to generate code.
  D. Use a natural language processing (NLP) tool to generate code.

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  Natural language processing (NLP) tools can be used to generate code from high-level descriptions or suggestions, which can greatly enhance software development productivity. By leveraging NLP models, developers can automate repetitive coding tasks, generate code snippets, or even complete blocks of code based on natural language inputs. This can speed up development and reduce errors.

• Question 217:

  A medical company deployed a disease detection model on Amazon Bedrock. To comply with privacy policies, the company wants to prevent the model from including personal patient information in its responses. The company also wants to receive notification when policy violations occur.

  Which solution meets these requirements?

  A. Use Amazon Macie to scan the model's output for sensitive data and set up alerts for potential violations.
  B. Configure AWS CloudTrail to monitor the model's responses and create alerts for any detected personal information.
  C. Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms for notification of policy violations.
  D. Implement Amazon SageMaker Model Monitor to detect data drift and receive alerts when model quality degrades.
  C. Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms for notification of policy violations.

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  Guardrails for Amazon Bedrock provide mechanisms to filter and control the content generated by models to comply with privacy and policy requirements. Using guardrails ensures that sensitive or personal information is not included in the model's responses. Additionally, integrating Amazon CloudWatch alarms allows for real-time notification when a policy violation occurs.

  Option C (Correct): "Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms for notification of policy violations":This is the correct answer because it directly addresses both the prevention of policy violations and the requirement to receive notifications when such violations occur.

  Option A:"Use Amazon Macie to scan the model's output for sensitive data" is incorrect because Amazon Macie is designed to monitor data in S3, not to filter real-time model outputs.

  Option B:"Configure AWS CloudTrail to monitor the model's responses" is incorrect because CloudTrail tracks API activity and is not suited for content moderation.

  Option D:"Implement Amazon SageMaker Model Monitor to detect data drift" is incorrect because data drift detection does not address content moderation or privacy compliance.

  References:

  Guardrails in Amazon Bedrock:AWS provides guardrails to ensure AI models comply with content policies, and using CloudWatch for alerting integrates monitoring capabilities.

• Question 218:

  A company has a team of AI practitioners that builds and maintains AI applications in an AWS account.

  The company must keep records of the actions that each AI practitioner takes in the AWS account for audit purposes.

  Which AWS service will meet these requirements?

  A. AWS CloudTrail
  B. AWS Config
  C. AWS Audit Manager
  D. AWS Trusted Advisor
  A. AWS CloudTrail

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  Explanation

  AWS CloudTrail records and logs all API calls and user actions in an AWS account, providing a complete audit trail of activities performed by each AI practitioner for compliance and audit purposes.

• Question 219:

  A company stores customer data in OpenSearch. The company wants an AI solution to retrieve specific customer information from the stored data. The AI solution must convert queries into data requests and generate CSV files from the results. Then, the AI solution must upload the CSV files to Amazon S3.

  Which solution will meet these requirements in the MOST operationally-efficient way?

  A. Create an AI agent to perform the required steps.
  B. Use a single foundation model (FM) with few-shot prompting.
  C. Create a software application without using AI to perform the required steps.
  D. Train a decision tree model to generate a solution based on user questions.
  A. Create an AI agent to perform the required steps.

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  Explanation

  An AI agent can orchestrate multiple actions end to end, including translating user queries into OpenSearch requests, generating CSV files from the results, and uploading the files to Amazon S3, making it the most operationally efficient approach.

• Question 220:

  A company is using an Amazon Nova Canvas model to generate images. The model generates images successfully.

  The company needs to prevent the model from including specific items in the generated images. Which solution will meet this requirement?

  A. Use a higher temperature value.
  B. Use a more detailed prompt.
  C. Use a negative prompt.
  D. Use another foundation model (FM).
  C. Use a negative prompt.

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  A negative prompt is used to specify items or characteristics that you want the image generation model to avoid including in the output, ensuring that specific items are excluded from generated images.