Machine Learning and Data Science with AWS 2023 - Hands On

Learn data science and machine learning services using AWS Athena, Glue, Quicksight, AWS Comprehend and Python Boto3

What you'll learn:

• You could prepare your dataset using AWS Glue, and Quicksight
• Perform Data Analysis using Athena
• Could Create Data Visualization Charts with Quicksight
• You could create and develop machine learning models using Natural Language Processing

Welcome to this course on Machine Learning and Data Science with AWS. Amazon Web services or AWS is one of the biggest cloud computing platform where everything gets deployed to scale and action. Understanding the concepts and methods are vital, but being able to develop and deploy those concepts in forms of real life applications is something that is most weighted by the industry. Thus, here in this course, we are focused on ways you can use various cloud services on AWS to actually build and deploy you ideas into actions on multiple domains on Machine Learning and Data Science. You could be an ITprofessional looking for job change or upgrading your skillset or you could be a passionate learner or cloud certification aspirant, this course is for wider audience that if formed by the people who would like to learn any of these or a combination of these things-

• Create and Analyze dataset to find insights and spot outliers or trends

• Build Data visualization reports and dashboards by combining various visualization charts to represent data insights

• Develop machine learning models for Natural Language Processing for various applications on AWS

• And much more.

Course Structure

This course consists of multiple topics that are arranged in multiple sections. In the first few sections you would learn cloud services related to Data Science and Analysis on AWS with hands on practical examples. There you would be learning about creating a crawler in Glue, Analyzing dataset using SQL in Amazon Athena. After that you would learn to prepare a dataset for creating Data Visualization charts and reports that can be used for finding critical insights from the dataset that can be used in decision making process. You will learn to create calculated fields, excluded lists and filters on AWS Quicksight, followed by some advanced charts such as Word cloud and Funnel chart.

After that in Machine Learning section, you will learn about Natural language processing and it's application with the help of AWS Comprehend and Translate. AWS Comprehend is used to identify the language of the text, extract key phrases, places, people, brands, or events, understand sentiment about products or services, and identify the main topics from a library of documents. AWSTranslate is used for translating language from one language to another.