AI1-C01 VALID BRAINDUMPS PDF | PASS-SURE AMAZON AI1-C01: AWS CERTIFIED AI PRACTITIONER EXAM

AI1-C01 Valid Braindumps Pdf | Pass-Sure Amazon AI1-C01: AWS Certified AI Practitioner Exam

AI1-C01 Valid Braindumps Pdf | Pass-Sure Amazon AI1-C01: AWS Certified AI Practitioner Exam

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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q25-Q30):

NEW QUESTION # 25
A company is implementing the Amazon Titan foundation model (FM) by using Amazon Bedrock. The company needs to supplement the model by using relevant data from the company's private data sources.
Which solution will meet this requirement?

  • A. Enable model invocation logging
  • B. Use a different FM
  • C. Choose a lower temperature value
  • D. Create an Amazon Bedrock knowledge base

Answer: D


NEW QUESTION # 26
A company is building a chatbot to improve user experience. The company is using a large language model (LLM) from Amazon Bedrock for intent detection. The company wants to use few-shot learning to improve intent detection accuracy.
Which additional data does the company need to meet these requirements?

  • A. Pairs of user messages and correct user intents
  • B. Pairs of user messages and correct chatbot responses
  • C. Pairs of user intents and correct chatbot responses
  • D. Pairs of chatbot responses and correct user intents

Answer: A


NEW QUESTION # 27
A company wants to use a large language model (LLM) on Amazon Bedrock for sentiment analysis.
The company wants to classify the sentiment of text passages as positive or negative.
Which prompt engineering strategy meets these requirements?

  • A. Provide the new text passage with a few examples of unrelated tasks, such as text summarization or question answering.
  • B. Provide the new text passage to be classified without any additional context or examples.
  • C. Provide examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified.
  • D. Provide a detailed explanation of sentiment analysis and how LLMs work in the prompt.

Answer: C


NEW QUESTION # 28
A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company wants to fine-tune the model to be more accurate by using the company's data.
Which strategy will successfully fine-tune the model?

  • A. Purchase Provisioned Throughput for Amazon Bedrock.
  • B. Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format.
  • C. Provide labeled data with the prompt field and the completion field.
  • D. Train the model on journals and textbooks.

Answer: C


NEW QUESTION # 29
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 Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms fornotification of policy violations.
  • C. Use Amazon Macie to scan the model's output for sensitive data and set up alerts for potential violations.
  • D. Configure AWS CloudTrail to monitor the model's responses and create alerts for any detected personal information.

Answer: B

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


NEW QUESTION # 30
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