# Data Analysis and Visualisation Courses

Data analysis and visualisation is an important aspect of commercial and scientific cloud and internet based applications. The value of large scale web ventures such as Google, Amazon, Facebook, LinkedIn and Twitter depends heavily on the fact that they collect vast amounts of data regarding the activities of their users and subscribers and gain valuable information and insights from the analysis of this data. These insights can be commercialised by use in e.g. focused advertising, or recommender systems. There are also large scale open source and open data systems such as those concerned with genomic research.

Over the last few decades various tools and techniques have been developed for analysing, mining and visualising these large data sets. More recently the emergence of various social networking ventures has stimulated research into using graph theoretic techniques to analyse various relationships to be deduced from the mass of social networking data available. A common approach to data analysis is to try and apply existing statistical data analysis, graph modeling and data mining techniques to larger and larger volumes of data. In practice scaling applications to ever larger volumes of data requires adapting of existing techniques and the development of distributed and parallel computing approaches to tackle the problems asscociated with scalability.

The courses in this section include covering widely used data analysis tools and techniques such as R, Python scientific and data analysis packages, as well as courses covering the data visualisation capabilities of R, various Python packages such as Matplotlib, and web oriented data visualisation tools such as D3.