Visual Analytics aims to facilitate the data analytics process through Information Visualisation. Information Visualisation aims to make good pictures of abstract information, such as stock prices, family trees, and software design diagrams. Well designed pictures can convey this information rapidly and effectively. The challenge for Visual Analytics is to design and implement effective Visualisation methods that produce pictorial representation of complex data so that data analysts from various fields (bioinformatics, social network, software visualisation and network) can visually inspect complex data and carry out critical decision making. This unit will provide basic HCI concepts, visualisation techniques and fundamental algorithms to achieve good visualisation of abstract information. Further, it will also provide opportunities for academic research and developing new methods for Visual Analytic methods.
Unit details and rules
Academic unit | Computer Science |
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Credit points | 6 |
Prerequisites
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(COMP2123 or COMP2823) and 126 credit points |
Corequisites
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None |
Prohibitions
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COMP5048 OR OCMP5048 |
Assumed knowledge
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None |
Available to study abroad and exchange students | Yes |
Teaching staff
Coordinator | Masahiro Takatsuka, masa.takatsuka@sydney.edu.au |
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