LATEST AMAZON AI1-C01 EXAM TIPS | LATEST AI1-C01 EXAM OBJECTIVES

Latest Amazon AI1-C01 Exam Tips | Latest AI1-C01 Exam Objectives

Latest Amazon AI1-C01 Exam Tips | Latest AI1-C01 Exam Objectives

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Tags: Latest AI1-C01 Exam Tips, Latest AI1-C01 Exam Objectives, AI1-C01 Certification Test Questions, AI1-C01 Latest Braindumps Pdf, AI1-C01 Exam Materials

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>> Latest Amazon AI1-C01 Exam Tips <<

AI1-C01 Dumps Torrent: AWS Certified AI Practitioner Exam & AI1-C01 Exam Bootcamp

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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q57-Q62):

NEW QUESTION # 57
A digital devices company wants to predict customer demand for memory hardware. The company does not have coding experience or knowledge of ML algorithms and needs to develop a data-driven predictive model.
The company needs to perform analysis on internal data and external data.
Which solution will meet these requirements?

  • A. Store the data in Amazon S3. Create ML models and demand forecast predictions by using Amazon SageMaker built-in algorithms that use the data from Amazon S3.
  • B. Import the data into Amazon SageMaker Data Wrangler. Create ML models and demand forecast predictions by using SageMaker built-in algorithms.
  • C. Import the data into Amazon SageMaker Canvas. Build ML models and demand forecast predictions by selecting the values in the data from SageMaker Canvas.
  • D. Import the data into Amazon SageMaker Data Wrangler. Build ML models and demand forecast predictions by using an Amazon Personalize Trending-Now recipe.

Answer: C

Explanation:
I'll continue to format the rest. Let me know if you would like me to provide them all in one go or in parts.


NEW QUESTION # 58
A company has developed an ML model for image classification. The company wants to deploy the model to production so that a web application can use the model.
The company needs to implement a solution to host the model and serve predictions without managing any of the underlying infrastructure.
Which solution will meet these requirements?

  • A. Use Amazon SageMaker Serverless Inference to deploy the model.
  • B. Use Amazon CloudFront to deploy the model.
  • C. Use AWS Batch to host the model and serve predictions.
  • D. Use Amazon API Gateway to host the model and serve predictions.

Answer: A


NEW QUESTION # 59
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?

  • A. Mask the confidential data in the inference responses by using dynamic data masking.
  • B. Encrypt the confidential data in the custom model by using AWS Key Management Service (AWS KMS).
  • C. Delete the custom model. Remove the confidential data from the training dataset. Retrain the custom model.
  • D. Encrypt the confidential data in the inference responses by using Amazon SageMaker.

Answer: C


NEW QUESTION # 60
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. Implement Amazon SageMaker Model Monitor to detect data drift and receive alerts when model quality degrades.
  • B. Use Amazon Macie to scan the model's output for sensitive data and set up alerts for potential violations.
  • C. Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms fornotification of policy violations.
  • D. Configure AWS CloudTrail to monitor the model's responses and create alerts for any detected personal information.

Answer: C

Explanation:
I'll continue with more questions shortly. Stay tuned!


NEW QUESTION # 61
Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?

  • A. Ability to perform real-time analysis on streaming data
  • B. Scalable index management and nearest neighbor search capability
  • C. Support for geospatial indexing and queries
  • D. Integration with Amazon S3 for object storage

Answer: B


NEW QUESTION # 62
......

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