AI1-C01 TEST PASSING SCORE & EXAM AI1-C01 QUIZZES

AI1-C01 Test Passing Score & Exam AI1-C01 Quizzes

AI1-C01 Test Passing Score & Exam AI1-C01 Quizzes

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Tags: AI1-C01 Test Passing Score, Exam AI1-C01 Quizzes, AI1-C01 Exam Topics Pdf, Exam AI1-C01 Testking, AI1-C01 Lab Questions

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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q83-Q88):

NEW QUESTION # 83
Which metric measures the runtime efficiency of operating AI models?

  • A. Average response time
  • B. Training time for each epoch
  • C. Number of training instances
  • D. Customer satisfaction score (CSAT)

Answer: A


NEW QUESTION # 84
A student at a university is copying content from generative AI to write essays.
Which challenge of responsible generative AI does this scenario represent?

  • A. Hallucinations
  • B. Privacy
  • C. Plagiarism
  • D. Toxicity

Answer: C


NEW QUESTION # 85
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. Selecting the foundation model (FM) based on predefined criteria and metrics
  • D. Automatically calling multiple foundation models (FMs) and consolidating the results

Answer: B


NEW QUESTION # 86
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 Canvas. Build ML models and demand forecast predictions by selecting the values in the data from SageMaker Canvas.
  • C. Import the data into Amazon SageMaker Data Wrangler. Create ML models and demand forecast predictions by using SageMaker built-in algorithms.
  • 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: B

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 # 87
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. Train the model on journals and textbooks.
  • C. Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format.
  • D. Provide labeled data with the prompt field and the completion field.

Answer: D


NEW QUESTION # 88
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