The Centre for Environmental Mathematics leads four MSc programmes on Applied Data Science for addressing Grand Challenges. These programmes are aimed at those looking to develop and apply modern techniques from data science and artificial intelligence in an interdisciplinary context, with a focus on energy, health, environment and conservation. Applicants are encouraged equally from the life, social and environmental sciences (including those who may not have much experience in scientific computing and mathematical modelling) and the engineering, maths and physical sciences. This diverse cohort of students helps foster the important interdisciplinarity.
The programmes employ research-informed, challenge-led and solution-focussed learning in collaboration with internationally renowned researchers at the Environment and Sustainability Institute, Renewable Energy Group, and Centre for Ecology and Conservation at the University’s Penryn Campus. There are four themes, described in more detail below: Environment and Sustainability, Modelling, Renewable Energy and Ecology and Evolution.
MSc Applied Data Science and Modelling
This programme provides students with an understanding of and confidence in using real-world data and mathematical models to address the big societal issues of the 21st Century. This is an interdisciplinary and outward facing programme run by the department of Mathematics in collaboration with science and engineering, which will encourage and support students to collaborate with industry, charities or public sector organisations. Through hands-on solution-focussed learning, in collaboration with internationally renowned investigators at the university's Environment and Sustainability Institute, European Centre for Environment and Human Health, and Department of Ecology and Conservation, students will gain skills and experience and so be able to succeed in the fast growing data analytics sectors, particularly in relation to health, energy and environment challenges.
MSc Applied Data Science (Environment and Sustainability)
This programme equips students with an understanding of state-of-the-art modelling and emergent data science techniques, and how to apply these to challenge-led problems focussed on economic, environmental, and societal issues surrounding sustainability practices and policies. The programme is hosted by the Environment and Sustainability Institute, where students are immersed in the institute's cutting-edge research on problems of environmental change, with opportunities to work with industry, charities and the public sector. With key data analytic skills and an understanding of sustainable development principles, two top priorities for many industries and many public and non-governmental organisations, the national and international demand for graduates of this programme will continue to grow.
MSc Applied Data Science (Renewable Energy)
Become immersed in the 'Big Data revolution' and develop state-of-the-art data science and artificial intelligence skills alongside expertise in emerging renewable technologies. This interdisciplinary programme is run jointly by the departments of Mathematics and Renewable Energy. Designed in collaboration with internationally renowned researchers and industrial partners, students will benefit from research-led teaching, practical examples and hands-on activities using modern scientific computing software, the hub for data-intensive science and artificial intelligence provided by the Institute of Data Science and Artificial Intelligence, a new state-of-the-art Renewable Energy Engineering Facility, and the interdisciplinary climate of the University's Environment and Sustainability Institute. Graduates will develop sought-after, discipline-transcending skills needed to succeed in the fast growing data analytics sectors, alongside specialist knowledge of value to the growing renewable energy sector.
MSc Applied Data Science (Ecology and Evolution)
Students of this programme develop an expertise of data scientific methods in ecology, evolution, conservation, biodiversity, and epidemiology. This interdisciplinary programme is run jointly by the mathematicians and life scientists from the university's Environment and Sustainability Institute, the Institute of Data Science and Artificial Intelligence, and the Centre for Ecology and Conservation. Students are exposed to a wide variety of data and data analytics approaches, drawing on cutting-edge and internationally renowned research, and will be supported and encouraged to collaborate with industry, charities, and the public sector. Through hands-on solution-focussed learning, students will gain the skills and experience needed to succeed in the fast growing expansion of data analytics in ecology and evolution.
Alice (2019 graduate, PhD student at the University of Bath’s Accountable, Responsible and Transparent AI Centre for Doctoral Training)
I graduated from studying in Penryn in 2019 and I since managed to secure a place at University of Bath in the Accountable, Responsible and Transparent AI CDT. I am midway through my first year currently and thoroughly enjoying it!
I loved studying in Penryn, for me it was one of the only places doing my course and they are really open-minded about interdisciplinarity with expert lecturers in their fields. Also, I couldn’t have wished to study in a nicer place, the environment is really relaxing!
I would say that if you research the course thoroughly, talk to programme leaders and decide that it is the right one for you then you will be in safe hands throughout, and Cornwall is the perfect place to study.
Charlotte (2020 graduate, Medical Statistician in the NHS from Sep. 2021)
I am soon to begin working as a Medical Statistician in the NHS. I was fortunate to have previous work experience in my local hospital, due to being interested in Medical research. However, one of the biggest reasons I am where I am is due to the support and incredibly unique experiences I was able to have while studying at University of Exeter in Cornwall. Not only was I able to learn from incredible lecturers, studying modules that my peers didn't have the opportunity to study on other courses but it was the personal relationships that I was able to develop that really built my confidence. If it wasn't for the time and encouragement that my lecturers gave to me, I would definitely not have believed in myself enough to apply for this course.
The material you get to cover at Penryn is so unique compared to other courses. The way we were taught in Penryn was so clear and well structured, that we were able to delve into the more advanced topics and yet it was taught in a really accessible way for everyone.
Penryn is an incredible place to study with a close knit community, located in one of the most beautiful places in the UK. If you are still having doubts, don't hesitate to get in contact. The staff are really passionate about what they do and helped me so much when deciding to study there, even though it was quite daunting to move so far from home.
Dr Anastasios Argyropoulos (2014 PhD graduate, Public Health Intelligence Manager, Swindon Borough Council)
I did a PhD on real time online monitoring and control of anaerobic digestion, followed by a post doc where I developed models aimed to predict "harms" on hospital admission using data analytics and artificial intelligence – both at Exeter. I now work as a Public Health Intelligence Manager for Swindon Borough Council. This role involves leading the work of the public health intelligence team; planning, project managing and delivering corporate intelligence and insight projects; providing specialist health intelligence input to public health and NHS strategic planning; as well as supporting the public health team with commissioning and evaluation of services, projects and processes.
Working with data on a regular basis polished my abilities in generating insight using several tools and techniques while applying the most suitable ones depending on the questions I was trying to answer. Practicing, keeping in touch with current/widely used data analysis methods and their application, learning your audience and receiving mentorship will allow you to grow.
For students who might want to pursue a similar career, I recommend gaining exposure to lots and different in nature (data) problems, understanding a variety of data analysis methods, learning how to utilise open source software (e.g. Python, R, QGIS) to solve those problems and collaborate with others (e.g. GitHub), explore different ways to generate insight from data and finally develop the ability to present information to different audiences.
I highly recommend the Applied Data Science programmes offered by the University of Exeter since they are being delivered by experts in their respective fields and will provide applicants with a series of “tools” needed to tackle data science and modelling problems.
Emily (2020 graduate, AI Analyst at The Range)
I chose to study in Cornwall because I liked how green and rural it was, and how chilled out the whole pace of life is down there. I’m not a city person, so Penryn was the perfect fit for me!
What I loved most about my degree was that we were a small cohort, so the lecturers knew us all by name and we were able to easily ask questions and get help from them. I also enjoyed all the maths celebrations we did like Pi and Fibonacci day, and I’ve made some wonderful friends from the experience.
If I were to give advice to anyone thinking of applying to study Applied Data Science I would say, do it! It will become such an essential skill to have for the future, with more and more people/companies realising the value of data and the power of data science, you really will be in high demand after you graduate!