AWS Certified AI Practitioner

• #21Choose 2

  An ecommerce company wants to build a solution to determine customer sentiments based on written customer reviews of products. Which AWS services meet these requirements? (Choose two.)

  • AAmazon Lex
  • BAmazon Comprehend.
  • CAmazon Polly.
  • DAmazon Bedrock.
  • EAmazon Rekognition.
  Show answer
• #22

  A company wants to display the total sales for its top-selling products across various retail locations in the past 12 months. Which AWS solution should the company use to automate the generation of graphs?

  • AAmazon Q in Amazon EC2.
  • BAmazon Q Developer.
  • CAmazon Q in Amazon QuickSight.
  • DAmazon Q in AWS Chatbot.
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• #23Choose 2

  A company wants to deploy a conversational chatbot to answer customer questions. The chatbot is based on a fine-tuned Amazon SageMaker JumpStart model. The application must comply with multiple regulatory frameworks. Which capabilities can the company show compliance for? (Choose two.)

  • AAuto scaling inference endpoints.
  • BThreat detection.
  • CData protection.
  • DCost optimization.
  • ELoosely coupled microservices.
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• #24Choose 2

  A loan company is building a generative AI-based solution to offer new applicants discounts based on specific business criteria. The company wants to build and use an AI model responsibly to minimize bias that could negatively affect some customers. Which actions should the company take to meet these requirements? (Select TWO.)

  • ADetect imbalances or disparities in the data.
  • BEnsure that the model runs frequently.
  • CEvaluate the model’s behavior so that the company can provide transparency to stakeholders.
  • DUse the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) technique to ensure that the model is 100% accurate.
  • EEnsure that the model’s inference time is within the accepted limits.
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• #25

  A company wants to use generative AI to increase developer productivity and software development. The company wants to use Amazon Q Developer. What can Amazon Q Developer do to help the company meet these requirements?

  • ACreate software snippets, reference tracking, and open-source license tracking.
  • BRun an application without provisioning or managing servers.
  • CEnable voice commands for coding and providing natural language search.
  • DConvert audio files to text documents by using ML models.
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• #26

  A financial institution is using Amazon Bedrock to develop an AI application. The application is hosted in a VPC. To meet regulatory compliance standards, the VPC is not allowed access to any internet traffic. Which AWS service or feature will meet these requirements?

  • AAWS PrivateLink.
  • BAmazon Macie.
  • CAmazon CloudFront.
  • DInternet gateway.
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• #27

  A company has a foundation model (FM) that was customized by using Amazon Bedrock to answer customer queries about products. The company wants to validate the model's responses to new types of queries. The company needs to upload a new dataset that Amazon Bedrock can use for validation. Which AWS service meets these requirements?

  • AAmazon S3.
  • BAmazon Elastic Block Store (Amazon EBS).
  • CAmazon Elastic File System (Amazon EFS).
  • DAWS Snowcone.
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• #28

  A company wants to build an ML model by using Amazon SageMaker. The company needs to share and manage variables for model development across multiple teams. Which SageMaker feature meets these requirements?

  • AAmazon SageMaker Feature Store.
  • BAmazon SageMaker Data Wrangler.
  • CAmazon SageMaker Clarify.
  • DAmazon SageMaker Model Cards.
  Show answer
• #29

  A company wants to use AI to protect its application from threats. The AI solution needs to check if an IP address is from a suspicious source. Which solution meets these requirements?

  • ABuild a speech recognition system.
  • BCreate a natural language processing (NLP) named entity recognition system.
  • CDevelop an anomaly detection system.
  • DCreate a fraud forecasting system.
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• #30

  A law firm wants to build an AI application by using large language models (LLMs). The application will read legal documents and extract key points from the documents. Which solution meets these requirements?

  • ABuild an automatic named entity recognition system.
  • BCreate a recommendation engine.
  • CDevelop a summarization chatbot.
  • DDevelop a multi-language translation system.
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• #31

  A company is building an application that needs to generate synthetic data that is based on existing data. Which type of model can the company use to meet this requirement?

  • AGenerative adversarial network (GAN).
  • BXGBoost.
  • CResidual neural network.
  • DWaveNet.
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• #32

  Which option is a use case for generative AI models?

  • AImproving network security by using intrusion detection systems.
  • BCreating photorealistic images from text descriptions for digital marketing.
  • CEnhancing database performance by using optimized indexing.
  • DAnalyzing financial data to forecast stock market trends.
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• #33

  A company has petabytes of unlabeled customer data to use for an advertisement campaign. The company wants to classify its customers into tiers to advertise and promote the company’s products. Which methodology should the company use to meet these requirements?

  • ASupervised learning.
  • BUnsupervised learning.
  • CReinforcement learning.
  • DReinforcement learning from human feedback (RLHF).
  Show answer
• #34

  Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?

  • AIntegration with Amazon S3 for object storage.
  • BSupport for geospatial indexing and queries.
  • CScalable index management and nearest neighbor search capability.
  • DAbility to perform real-time analysis on streaming data.
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• #35

  What are tokens in the context of generative AI models?

  • ATokens are the basic units of input and output that a generative AI model operates on, representing words, subwords, or other linguistic units.
  • BTokens are the mathematical representations of words or concepts used in generative AI models.
  • CTokens are the pre-trained weights of a generative AI model that are fine-tuned for specific tasks.
  • DTokens are the specific prompts or instructions given to a generative AI model to generate output.
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• #36

  A company built a deep learning model for object detection and deployed the model to production. Which AI process occurs when the model analyzes a new image to identify objects?

  • ATraining.
  • BInference.
  • CModel deployment.
  • DBias correction.
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• #37

  An AI practitioner is using a large language model (LLM) to create content for marketing campaigns. The generated content sounds plausible and factual but is incorrect. Which problem is the LLM having?

  • AData leakage.
  • BHallucination.
  • COverfitting.
  • DUnderfitting.
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• #38

  An AI company periodically evaluates its systems and processes with the help of independent software vendors (ISVs). The company needs to receive email message notifications when an ISV's compliance reports become available. Which AWS service can the company use to meet this requirement?

  • AAWS Audit Manager.
  • BAWS Artifact.
  • CAWS Trusted Advisor.
  • DAWS Data Exchange.
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• #39

  How can companies use large language models (LLMs) securely on Amazon Bedrock?

  • ADesign clear and specific prompts. Configure AWS Identity and Access Management (IAM) roles and policies by using least privilege access.
  • BEnable AWS Audit Manager for automatic model evaluation jobs.
  • CEnable Amazon Bedrock automatic model evaluation jobs.
  • DUse Amazon CloudWatch Logs to make models explainable and to monitor for bias.
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• #40

  An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate inference responses based on confidential data. How should the AI practitioner prevent responses based on confidential data?

  • ADelete the custom model. Remove the confidential data from the training dataset. Retrain the custom model.
  • BMask the confidential data in the inference responses by using dynamic data masking.
  • CEncrypt the confidential data in the inference responses by using Amazon SageMaker.
  • DEncrypt the confidential data in the custom model by using AWS Key Management Service (AWS KMS).
  Show answer

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