MSc Environmental Intelligence

at University of Exeter

Environmental Intelligence is the integration of Environmental and sustainability research with Data Science, Artificial Intelligence and cutting-edge digital technologies to provide organisations with the meaningful insight required to address the challenges associated with environmental and climate change.
 

We will provide you with training in the three core components of Environmental Intelligence: data science and artificial intelligence, environmental challenges, and the use of data in society. Core modules introducing data science, statistical modelling and machine learning will be delivered using environmental examples and will be accompanied by modules covering the communication of data science, ethics and governance.
 

You will be able to choose from a range of optional modules covering topics such as digital business models, high-performance computing, food systems, business and climate change and innovation and the science-policy interface.
 

In addition to the taught component of the programme, you will be able to apply your newly developed skills in an extended piece of research allowing you to focus on an area that is of particular interest to you. During this time you will have the opportunity to work directly with experts from across the University of Exeter and, for certain projects, with experts from the Met Office.
 

The modules we outline here provide examples of what you can expect to learn on this degree course based on recent academic teaching. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand.

Compulsory modules

• Environmental Intelligence: Data
• Environmental Intelligence: Methods and Models
• Topics in Environmental Intelligence
• Communicating Data Science
• Working with Data
• Data Governance and Ethics
• Environmental Intelligence Research Project

Successful applicants will usually have at least a 2:1 in their undergraduate degree, but we will consider alternative qualifications and experiences and all applicants are considered on their individual merits.
 

Applicants must have an A level or equivalent in Mathematics and/or have received quantitative skills training as part of their undergraduate programme or professional experience.
 

Prior experience of coding is not necessary on this course.

English Language Requirements
 

• IELTS

  Overall score 6.5. No less than 6.0 in any section.
   

• TOEFL

  Overall score 90 with minimum scores of 21 for writing, 21 for listening, 22 for reading and 23 for speaking.

UK fees per year:
£11,500 full-time
 

International fees per year:
£24,500 full-time
 

Please note: For certain projects, students may have the opportunity to conduct research projects in collaboration with a supervisor from the Met Office and therefore may incur some additional, minimal, travel costs.

Employer-valued skills this course develops

You will gain the skills to be able to fully utilise Data Science and Artificial Intelligence in addressing the challenges associated with environmental and climatic change through a truly inter-disciplinary delivery of environmental and technical knowledge, together with the use of environmental intelligence in practice.
 

You will develop the skills in Data Science and Artificial Intelligence, together with environmental knowledge, which will be key to success in both government and business and developing sustainable interactions with the natural environment.
 

Career paths

Our interaction with the natural environment plays a crucial role in all aspects of society: our health, wealth, safety and future prosperity. Environmental and climate change, and the need to transition to a Net Zero economy, means businesses and governments will need access to decision-critical information on the environment to survive and thrive.
 

Environmental Intelligence solutions will become business-critical across many sectors, including energy, transportation, agriculture, critical infrastructure, telecommunications and healthcare.