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Component
MSc Big Data and Text Analytics options
Year 1, Component 08
Option from list
CE708-7-AU
Computer Security
(15 CREDITS)
This course gives an introduction to computer security and cryptography, and then goes on to consider security as it relates to a single, network connected, computer. Introductory material is independent of any operating system but the consideration of tools will focus on those available for Linux, partly because its open-source nature facilitates this and partly because it is widely used on server systems. The introduction to cryptography will be used to consider its use in encryption and authentication.
A huge industry has grown up in the last few years delivering a wide range of apps for mobile devices, including application areas such as games, social networking, information, and productivity. Given the power of modern mobile devices coupled with their range of inputs (audio, camera, GPS, motion sensor, touchscreen) this creates an exceptionally interesting platform to develop applications for. Furthermore, these platforms come complete with their own marketplaces meaning that successful applications can achieve a large market share based largely on their merit. The purpose of this module is to teach the main aspects of programming applications for such devices. Such a course could be taught at an abstract level, independent of the particular type of device in question, but the approach taken on this module is to explore one particular platform (Android), in a hands-on and in-depth manner. This is a popular platform with a range of excellent devices (including low cost ones) from a variety of manufacturers. The platform is well designed and well documented, and has the significant advantage of being Java based, meaning that students can get up to speed relatively quickly and concentrate on the interesting issues involved in developing a high quality app without having to learn a new language at the same time.
Mathematics is a tool used in many fields of research, and this module introduces students to techniques and ways of thinking designed to enable them to carry out their own mathematical investigations, or to apply mathematical ideas to an investigation of their own (typically for most students on this module, this will be their Dissertation project). We use the industry standard mathematical software Matlab, although the techniques introduced can also be applied using other software, and we study a range of techniques for numerical computation and processing of data.
The aim of this module is to familiarise students with the whole pipeline of processing, analysing, presenting and making decision using data. This module blends data analysis, decision making and visualisation with practical python programming. Students will need a reasonable programming background as they will be expected to develop a complete end-to-end data science application.
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