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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q14-Q19):

NEW QUESTION # 14
A company is using an Amazon Bedrock base model to summarize documents for an internal use case. The company trained a custom model to improve the summarization quality.
Which action must the company take to use the custom model through Amazon Bedrock?

A. Register the model with the Amazon SageMaker Model Registry.
B. Grant access to the custom model in Amazon Bedrock.
C. Purchase Provisioned Throughput for the custom model.
D. Deploy the custom model in an Amazon SageMaker endpoint for real-time inference.

Answer: D

NEW QUESTION # 15
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 to be classified without any additional context or examples.
B. Provide examples of text passages with corresponding positive or negative labels in the prompt followed by the new text passage to be classified.
C. Provide the new text passage with a few examples of unrelated tasks, such as text summarization or question answering.
D. Provide a detailed explanation of sentiment analysis and how LLMs work in the prompt.

Answer: B

NEW QUESTION # 16
A company wants to create an application by using Amazon Bedrock. The company has a limited budget and prefers flexibility without long-term commitment.
Which Amazon Bedrock pricing model meets these requirements?

A. Model customization
B. On-Demand
C. Spot Instance
D. Provisioned Throughput

Answer: B

NEW QUESTION # 17
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 API Gateway to host the model and serve predictions.
B. Use Amazon SageMaker Serverless Inference to deploy the model.
C. Use AWS Batch to host the model and serve predictions.
D. Use Amazon CloudFront to deploy the model.

Answer: B

NEW QUESTION # 18
An accounting firm wants to implement a large language model (LLM) to automate document processing.
The firm must proceed responsibly to avoid potential harms.
What should the firm do when developing and deploying the LLM? (Select TWO.)

A. Apply prompt engineering techniques.
B. Avoid overfitting on the training data.
C. Modify the training data to mitigate bias.
D. Include fairness metrics for model evaluation.
E. Adjust the temperature parameter of the model.

Answer: C,D

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

NEW QUESTION # 19
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Sample AI1-C01 Test Online | AI1-C01 Well Prep

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Amazon AWS Certified AI Practitioner Exam Sample Questions (Q14-Q19):

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