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This module briefs the Amazon Sagemaker, Amazon Comprehend, Amazon Lex, Amazon Polly, Amazon Recognition, Amazon Deeplens, and Amazon Textract components of AWS. 

AI can be created in a proprietary manner, and it's also not a necessity for a business solution. So why exactly should we use the AI services provided in AWS? Let's answer this question in this module.

AI and ML are two sides of the same coin and go hand in hand. So, let's look into some of the service domains provided in AWS for AI and ML services.

In the first module, you will understand the basics of a machine learning model that a Data Scientist prepares for data processing. You will also understand what AWS Sagemaker is and how it is used.

This module discusses the Architecture of the AWS Sagemaker and its applications. Later on, you will understand the data processing procedure.

In the last module, you will understand the dashboard of an AWS Sagemaker. Later on, the course demonstrates a sample program. You will learn about the steps for creating a data manipulation machine learning model by creating Jupyter notebook instances, uploading the datasets, and training the data model with the help of Machine Learning algorithms. 

Amazon Comprehend is an AWS service that develops insights by recognizing the common elements. Amazon Polly, on the other hand, is a Text-To-Speech synthesizer. Let's look into some of the most pertinent features of these services.

Amazon Textract is a text detection and analysis AI service provided by AWS. Amazon Transcribe is a speech recognizer and analyzer service provided by AWS. Let's look into some of the most pertinent features of these services.

Amazon Forecast delivers highly accurate time-series forecasts based on statistical and machine learning algorithms as an AWS service. Amazon Personalize is an AI-based AWS service that aids businesses in delivering personalized experiences to their users. Let's look into some of the most pertinent features of the both these services.