1. How can you integrate Amazon Lex with a third-party messaging application?

A) By using the AWS SDKs to develop a custom integration
B) By using the Amazon Lex Console to create a custom integration
C) By using the Amazon Lex REST API to create a custom integration
D) By using the Amazon Lex Bot Framework to create a custom integration
E) By using the Amazon Connect service to create a custom integration


2. Which of the following AWS Polly features allow you to customize the voice and pronunciation of synthesized speech?

A) Speech marks
B) Prosody
C) Lexicons
D) All of the above
E) None of the above


3. You are working on a project that requires detecting and analyzing faces in a large volume of images stored in Amazon S3. Which Amazon Rekognition feature can be used to achieve this?

A) Face Detection
B) Face Comparison
C) Face Search
D) Celebrity Recognition
E) Object and Scene Detection


4. You are tasked with building a machine learning model to predict whether a customer is likely to churn from a subscription-based service. The dataset contains millions of rows of transactional data, and you need to preprocess the data before building the model. Which of the following AWS SageMaker services would you use to preprocess the data at scale?

A) Amazon SageMaker Feature Store
B) Amazon SageMaker Ground Truth
C) Amazon SageMaker Data Wrangler
D) AWS Glue
E) Amazon EMR


5. Which AWS service would you use to extract handwriting text from scanned documents and forms?

A) Amazon Rekognition
B) Amazon Comprehend
C) Amazon Textract
D) Amazon SageMaker Ground Truth