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AIF-C01 Practice Test


Page 7 out of 21 Pages

A company is building a large language model (LLM) question answering chatbot. The company wants to decrease the number of actions call center employees need to take to respond to customer questions.
Which business objective should the company use to evaluate the effect of the LLM chatbot?


A. Website engagement rate


B. Average call duration


C. Corporate social responsibility


D. Regulatory compliance





B.
  Average call duration

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 Amazon API Gateway to host the model and serve predictions.


D. Use AWS Batch to host the model and serve predictions.





A.
  Use Amazon SageMaker Serverless Inference to deploy the model.

Explanation:
Amazon SageMaker Serverless Inference is the correct solution for deploying an ML model to production in a way that allows a web application to use the model without the need to manage the underlying infrastructure.
Amazon SageMaker Serverless Inference provides a fully managed environment for deploying machine learning models. It automatically provisions, scales, and manages the infrastructure required to host the model, removing the need for the company to manage servers or other underlying infrastructure.
Why Option A is Correct:
Why Other Options are Incorrect:
Thus, A is the correct answer, as it aligns with the requirement of deploying an ML model without managing any underlying infrastructure.

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?


A. Amazon Q in Amazon EC2


B. Amazon Q Developer


C. Amazon Q in Amazon QuickSight


D. Amazon Q in AWS Chatbot





C.
  Amazon Q in Amazon QuickSight

A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text.
Which type of model meets this requirement?


A. Topic modeling


B. Clustering models


C. Prescriptive ML models


D. BERT-based models





D.
  BERT-based models

Explanation: BERT-based models (Bidirectional Encoder Representations from Transformers) are suitable for tasks that involve understanding the context of words in a sentence and suggesting missing words. These models use bidirectional training, which considers the context from both directions (left and right of the missing word) to predict the appropriate word to fill in the gaps.

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. Provide labeled data with the prompt field and the completion field.


B. Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format.


C. Purchase Provisioned Throughput for Amazon Bedrock.


D. Train the model on journals and textbooks.





A.
  Provide labeled data with the prompt field and the completion field.


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