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Amazon AWS Certified AI Practitioner Sample Questions:

1. A company has built a chatbot that can respond to natural language questions with images. The company wants to ensure that the chatbot does not return inappropriate or unwanted images.
Which solution will meet these requirements?

A) Retrain the model with a general public dataset.
B) Perform model validation.
C) Implement moderation APIs.
D) Automate user feedback integration.

2. A company has thousands of customer support interactions per day and wants to analyze these interactions to identify frequently asked questions and develop insights.
Which AWS service can the company use to meet this requirement?

A) Amazon Comprehend
B) Amazon Lex
C) Amazon Translate
D) Amazon Transcribe

3. A company has built an image classification model to predict plant diseases from photos of plant leaves. The company wants to evaluate how many images the model classified correctly.
Which evaluation metric should the company use to measure the model's performance?

A) Accuracy
B) R-squared score
C) Learning rate
D) Root mean squared error (RMSE)

4. An AI practitioner is using an Amazon Bedrock base model to summarize session chats from the customer service department. The AI practitioner wants to store invocation logs to monitor model input and output data.
Which strategy should the AI practitioner use?

A) Configure AWS CloudTrail as the logs destination for the model.
B) Enable invocation logging in Amazon Bedrock.
C) Configure AWS Audit Manager as the logs destination for the model.
D) Configure model invocation logging in Amazon EventBridge.

5. 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 QuickSight
B) Amazon Q in Amazon EC2
C) Amazon Q Developer
D) Amazon Q in AWS Chatbot

Solutions: