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Data Science at UEA
Find out more about studying Data Science at UEA, and browse our other courses.
Find out moreMSc Data Science for Environmental Science
Key details
- Attendance
- Full Time
- Award
- Degree of Master of Science
- Course Length
- 1 year
- Course Start Date
- September 2027
Other Start Dates
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4th
UEA is ranked 4th overall for research quality in Earth Systems and Environmental Sciences
Times Higher Education REF 2021 AnalysisCourse Overview
Why MSc Data Science for Environmental Science at UEA?
Become a highly qualified data scientist with the knowledge and understanding to apply these skills to a wide range of careers relating to the environment. This course combines environmental science with in-depth tuition in data science, programming, and machine learning.
Why Choose UEA
- World-leading experts: Learn from internationally renowned scientists in a school ranked first in the UK for research quality
- Interdisciplinary science: Apply machine learning, data analysis, and programming to diverse environmental research topics
- Employability: Develop highly employable data science skills and subject expertise to support your chosen environmental career
What is Data Science for Environmental Science?
Data Science is a highly sought-after skillset that is widely used in modern organisations to understand the world around them. It’s recently become a key component of environmental science. Studying data science for environmental science will give you the skills and understanding to be an expert in using cutting-edge tools to solve some of the most important and complex challenges in the natural world.
Data science is used in a wide variety of environmental science applications, from big data analysis of climate model output to geospatial data analysis; from numerical modelling of environmental hazards to using machine learning to understand complex geophysical processes.
Data science is increasingly used by environment-facing companies, organisations and research institutes to understand the world around us, to make predictions of complex systems, and to make data-driven decisions.
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Careers
Career Pathways
With a MSc Data Science for Environmental Science degree, you could launch a career in:
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Environmental data scientist: Use machine learning and numerical modelling to understand and predict environmental systems
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GIS and data analyst: Collect, analyse, and visualise spatial data to support planning, decision-making, and problem-solving across diverse sectors
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Big data analyst: Manage and analyse very large data sets produced by remote sensing or numerical models
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Sustainability analyst: Provide data-driven analysis to help organisations improve their sustainability
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Climate data analyst: Analyze long-term trends and model projections to assist in climate adaptation and risk mitigation
Career Support
Employability is embedded across all our modules, helping you develop your career aspirations and skills throughout your course. We work closely with UEA’s Career Central(opens in a new window) to help you track and reflect on your activities via the UEA Award. You’ll also have opportunities to meet employers, explore your career options, speak to industry mentors, and apply for internships, volunteering, and exciting graduate jobs in data science.
After the Course
Upon graduating, you'll be a highly trained environmental data scientist. You’ll be well-equipped to take up rewarding positions across the public and private sector organisations, where you can use cutting-edge data science tools to provide solutions to today’s environmental challenges.
Study and Modules
Structure
Our MSc Data Science for Environmental Science course is a full-time, one-year taught programme, designed for advanced students and practitioners.
You’ll have an average of 15 hours of contact time per week with teaching staff, depending on your module choices. This will include lectures, seminars, and lab classes. Lab and seminar classes are an opportunity to reinforce and expand on the lecture material and will provide you with practical experience of data science methods.
The course has both theoretical and practical elements, so you’ll be given hands-on experience using data mining and statistical software. You'll learn to code in Python and R, two of the most popular programming languages in data science. You'll also learn about diverse environmental challenges, from climate change to natural hazards, from numerical modelling to environmental economics
Your dissertation will provide a capstone project to demonstrate your skills in using data science to investigate a cutting-edge environmental research topic of your choosing. This project will be the culmination of a degree that develops excellent problem-solving and data analysis skills that are highly prized by modern organisations needing to make data-driven decisions.
Compulsory Modules
Optional A Modules
(Min Credits: 0, Max Credits: 20)Optional B Modules
(Credits: 20)Optional C Modules
(Min Credits: 0, Max Credits: 20)Important Information
Whilst the University will make every effort to offer the modules listed, changes may sometimes be made arising from the annual monitoring, review and update of modules. Where this activity leads to significant (but not minor) changes to programmes and their constituent modules, the University will endeavour to consult with students and others. It is also possible that the University may not be able to offer a module for reasons outside of its control, such as the illness of a member of staff. In some cases optional modules can have limited places available and so you may be asked to make additional module choices in the event you do not gain a place on your first choice. Where this is the case, the University will inform students.
Teaching and Learning, and Assessment
Teaching and Learning
Our teaching is modular with a standard pattern of three modules per semester. Typically, a module will include two 50-minute lectures per week plus a practical or seminar class where you'll deepen your understanding of the material. You’ll conduct experiments in our state-of-the-art laboratories, and develop highly valued transferable skills in data analysis, spatial visualisation and science communication.
Your individual study will complement formal teaching and will evolve along with your skills and expertise in data analysis.
Assessment
Each module has its own assessment structure to ensure you meet the learning outcomes. Most modules (including all compulsory modules) are primarily assessed by coursework, with some in-class tests, presentations, and oral exams. Examples include data science analysis projects using Python and R, preparation of policy briefs, environmental modelling projects, and essay-based analysis of topical issues in environmental science.
In all cases, formative (practice) assessments are offered in each area to help you develop your skills and abilities before completing the summative assessment that counts towards your degree grade.
Entry Requirements
- This course is open to
UK and International fee-paying students. Choose UK or International above to see relevant information. The entry point is in September each year.
- Typical UK Entry Requirements
Degree classification
Bachelors degree - 2.2.
Degree Subject
Any science subject across physical and social sciences. Strong applicants from other backgrounds with experience relevant to Environmental Sciences or Data Science are also encouraged to apply.
- Admissions Policy
Our Admissions Policy applies to the admissions of all postgraduate applicants.
- This course is open to
UK and International fee-paying students. Choose UK or International above to see relevant information. The entry point is in September each year.
- Typical International Entry Requirements
Degree classification
UK Bachelors degree - 2.2 or equivalent
Degree Subject
Any science subject across physical and social sciences. Strong applicants from other backgrounds with experience relevant to Environmental Sciences or Data Science are also encouraged to apply.
- English Foreign Language
Applications from students whose first language is not English are welcome. We require evidence of proficiency in English (including writing, speaking, listening and reading):
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IELTS: 6.0 overall with minimum 5.5 in each component.
We also accept a number of other English language tests. Review our English Language Equivalencies(opens in a new window) for a list of example qualifications that we may accept to meet this requirement.
Test dates should be within two years of the course start date.
If you do not meet the English language requirements for this course, UEA International Study Centre offers a variety of English language programmes which are designed to help you develop the required English skills.
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- Admissions Policy
Our Admissions Policy applies to the admissions of all postgraduate applicants.
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Fees and Funding
Tuition fees for the Academic Year 2027/28 are:
- UK Students: £12,950
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International Students: £27,000
We estimate living expenses at £1,171 per month.
Further Information on tuition fees can be found here(opens in a new window).
Scholarships and Bursaries
The University of East Anglia offers a range of Scholarships(opens in a new window); please click the link for eligibility, details of how to apply and closing dates.
Course Related Costs
Please see Additional Course Fees(opens in a new window) for details of course-related costs.
How to Apply
How to apply
Applications for Postgraduate Taught programmes at the University of East Anglia should be made directly to the University.
To apply please use our online application form(opens in a new window).
Further information
If you would like to discuss your individual circumstances prior to applying, please do contact us:
Postgraduate Admissions Office
Tel: +44 (0)1603 591515
Email: admissions@uea.ac.uk(opens in a new window)
International candidates are also encouraged to access the International Students(opens in a new window) section of our website.