Course Details in 2024/25 Session

Module Title	LM Data Visualisation
School	Mathematics
Department	Mathematics
Module Code	06 40202
Module Lead	TBC
Level	Masters Level
Credits	10
Semester	Semester 1
Pre-requisites
Co-requisites
Restrictions	None
Contact Hours	Lecture-24 hours Guided independent study-76 hours Total: 100 hours
Exclusions
Description	Well-designed visualisations leverage our innate ability to process visual data, enhancing understanding, recall, reasoning, and decision-making. With the surge in \"Big Data,\" the demand for potent visualisation systems for data interpretation and communication has grown. This module focuses on methods and algorithms for data visualisation. Specific topics include basic data charts and their applicability for different data types, interactive visualisations, visualisation of specific data sets, visualisation for data quality inspection. To deal with the visualisation of raw data, data cleansing and other pre-processing methods will also be covered.
Learning Outcomes	By the end of the module students should be able to: Grasp the main visualisation techniques and theory, including how data is structured, how we visually understand information, and methods for visual encoding and interaction. Work with various types of data and learn how to visualise them using different visualisation techniques. Apply suitable data visualisation methods to real-world data and extract information from it.
Assessment
Assessment Methods & Exceptions	Assessment: 80% examination, 20% coursework. Reassessment: Resit exam
Other
Reading List