|School or Department :||School of Mathematics, Physics & Computing|
|Grading basis :||Graded|
|Course fee schedule :||https://www.unisq.edu.au/current-students/administration/fees/fee-schedules|
|Version produced :||4 October 2023|
Government, private enterprise and science have been collating large amounts of data, and visualisation is a crucial part of knowing that data, though it needs to be done correctly so as to not mislead those who seek to make use of the data. Many organisations strive to collect as much data as possible, to see later what insights it might hold. This rapidly growing field, referred to as Big Data, is a rapidly evolving field. Visualising data comes in many forms, but consideration is required when compiling huge amount of data into a meaningful and visual display. Those who work to create a visual presentation require technical background need a knowledge of the data, its meaning, and best principles to apply to create usable, meaningful, and honest representations.
This course covers the fundamental principles of data science concepts and introduces the student to some of its common tools, methodologies and visualisations. Students will learn how to extract knowledge from data through hands-on experience with common data science programming tools and methodologies. They will create data visualisations to conduct exploratory and confirmatory data analysis. And will gain an appreciation of the breadth of data science applications and their potential value across disciplines.