This course covers the basic to advanced data visualization techniques. It is designed for students having no or very little experience in the field of data analytics. The course is divided into 11 modules. Starting from the very basic introduction of data visualization and data analytics and explains the difference amongst the two. Later the course covers all steps for setting the accounts of AWS and Quicksight to allow the students to get started using the visualization tool. Followed by an introduction of both AWS and Quicksight and a detailed overview of the tool. All the major types of visualizations and analysis are covered which are dealt by data analysts on a day to day basis alongwith the types of data that is represented effectively using these visuals .

Importing data from multiple sources, data preparation and transformation is covered in this course. Visualization structures such as tables and pivot tables are covered in depth with the help of various lab sessions. To be able to add calculated fields using the existing data is a very strong pursuit of a data analyst, this aspect has been covered in depth and repeatedly throughout the lab sessions. Then there are some important features of Quicksight namely, filters and controls which are explained accompanied with their respective types using practical examples. Each section is covered using the practical lab sessions.

The course has a capstone project at the end which explains the start to end workflow of data visualization using Quicksight, after which the student is able to gain practical insight to the course.

By the end of this course students will emerge with a solid understanding of data visualization and analytics using AWS Quicksight and hands-on experience designing analysis and visualization.

All the lab resources for this course can be found on our git repository.