SDSC5002 - Exploratory Data Analysis and Visualization

Offering Academic Unit
School of Data Science
Credit Units
Course Duration
One Semester
Course Offering Term*:
Semester A 2021/22

* The offering term is subject to change without prior notice
Course Aims

The goal of this course is to introduce students to the essential exploratory techniques for summarizing data and associated visual methods. Exploratory data analysis is typically applied before formal modelling commences. It can help formulate hypotheses and inform the development of more complex statistical models. The course begins with an introduction of basic graphical techniques used in exploratory data analysis, continues with typical statistical methods for exploratory analysis including clustering and dimension reduction techniques that allow you to make graphical displays of high dimensional data, then focuses on visualization techniques and methods for a broad range of data types. Principles from perception will be introduced to design effective data visualizations. Students will work through a series of case studies and hands-on projects to learn the skills for working with real-world data. 

Assessment (Indicative only, please check the detailed course information)

Continuous Assessment: 100%
Detailed Course Information


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School of Data Science