Environmental Data Science is developing into an increasingly important professional specialism, where large datasets of spatial and temporal information are assembled and manipulated in order to improve the understanding and management of complex environmental systems. However, the sheer volumes of data collected, often termed ‘big data’, challenge traditional methods for structuring, manipulating and outputting information for decision makers. Such data is gathered by modern real-time sensors and data loggers, satellite and aerial remote observation platforms, machinery, and simulation outputs such as climate-change modelling applications. The Environmental Data Science course will supply graduates with the practical skills and capabilities necessary to manage and manipulate such ‘big data’ to provide effective information tailored to the management of environmental systems. The objective of the course is to supply students with practical routes to establish and communicate meaningful outcomes from ‘big data’ to the user communities served, using the latest generation of information manipulation and visualisation techniques. The course represents an exciting combination of rigorous academic, technical and practical training, providing a thorough training in the technical, analytical and research skills needed for a career in this expanding field. "MSc Full-time - £17,500 PgDip Full-time - £14,000 PgCert Full-time - £7,000"

The UK has one of the world's strongest digital markets and data, in all its forms, is now so important in organisations that analysts rate it as a major competitive advantage (The Independent). The ICT, software and digital content sectors are together worth £100bn. The UK digital economy is estimated to be larger per head than in any other country and it is expected to grow to 10% of GDP by 2015 (Technology Strategy Board). In Europe as a whole, ‘Big Data’ is estimated to generate significant financial value to the tune of EUR250bn per year across the public sector (McKinsey Global Institute). In the UK, there are estimates in which the digital economy accounts for nearly £1 in every £10 that the UK economy produces each year (Dept. for Culture, Media and Sport). There are clear government efforts (eg. cross-research council ‘Digital Economy’ or Technology Strategy board ‘Connected Digital Economy Catapult’ to promote and support the digital economy). Sustainable development is one of the key themes noted in many of the strategy statements and growth outcomes. In these same studies (and others), key skills required are those associated with Modelling, Multi-disciplinarity, Data Management and Numeracy (ERFF). Stated more simply by the UK Department for Business, Innovation and Skills (BIS), this equates to the fields of science, technology, engineering and mathematics. The Digital Economy will require graduates with the technical skills to manage, manipulate and visualize large datasets (IT technology and engineering) and interpret and represent this data as information and knowledge (science and mathematics). However, currently a ‘significant constraint on realising value from big data will be a shortage of talent’ (McKinsey Global Institute).