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MScEnvironmental Data Science

Cranfield University
United Kingdom, Cranfield
Tuition fee To be confirmed
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Environmental Data Science is developing into an increasingly important professional specialism. This course will supply graduates with the practical skills and capabilities necessary to manage and manipulate ‘big data’ to provide effective information tailored to the management of environmental systems.

The Environmental Data Science course aims to provide a professional level of training in the technical, analytical and research skills and knowledge required to enhance your career prospects within the dynamic field of environmental information management.

The course will focus on the handling of large environmental datasets, or ‘big data’, emphasising emergent techniques in environmental data interpretation, data mining, predictive analytics, and web delivery, all tailored to the rational management of environmental systems.

The course objectives are 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 – Develop to a professional level expertise in data fusion and information management, techniques to support the statistical interpretation, utilisation and interoperability of multiple data sources in providing a combined representation of environmental conditions – Provide access to data-derived knowledge in appropriate form for engagement with users through application of web-based, service oriented computing architectures used to provide access to such resources across the internet – Integrate, within the context of a specific project, appropriate elements of the component technologies to produce quality-assured and innovative informatics solutions.

Programme structure

This course comprises eight taught modules, a group project and an individual project. The taught modules consist of lectures, tutorials, demonstrations and practical classes taken during the autumn and spring. Each module forms the sole unit of study for a period of two weeks. An opportunity to undertake a project in the style of a consultancy project is offered on the full-time programme and is conducted from mid February to April.

Career opportunities

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 (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, e.g. 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 visualise 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).

Cranfield graduates from this course can expect to follow a wide range of career paths in academic research or professional environmental management; environmental consultancy with private firms, non-profit organizations and government. Environmental Data Science will furthermore provide for an enhancement of skill sets for mid-career professionals as it represents an emerging set of quantitative tools which achieve concrete solutions to trans-disciplinary problems.

Apply now! Fall semester 2021/22
This intake is not applicable

We are currently NOT ACCEPTING applications from NON-EU countries, except Georgia and Serbia.

Application deadlines apply to citizens of: United States

Apply now! Fall semester 2021/22
This intake is not applicable

We are currently NOT ACCEPTING applications from NON-EU countries, except Georgia and Serbia.

Application deadlines apply to citizens of: United States