Course overview
Tackle complex global environmental challenges using data science and machine learning methods.
Today’s biggest environmental challenges, such as climate change, sustainability and clean energy, increasingly rely on data-driven solutions. At the same time, employers are looking for people who can combine environmental understanding with strong data and analytical skills.
As the environmental technology sector continues to grow, employers worldwide face a shortfall of skilled professionals. Although machine learning adoption is widespread, many organisations struggle to move models from development into practical application.
Our Environmental Data Science with Machine Learning MSc is designed to address this shortfall by developing graduates who can combine deep environmental insight with the computational rigour needed not only to build predictive models but also to successfully deploy them effectively in real-world settings.
Throughout the course, you’ll develop a broad understanding of environmental issues and how data-driven analysis can help address them. The programme gives you an in-depth understanding of data and what effective interpretation and insight generation mean across diverse environmental contexts.
You’ll build the skills needed to analyse, understand, interpret, and visualise complex datasets. Moving beyond standard data visualisation, you will apply techniques from data science, including environmental modelling, machine learning, geospatial analytics, and data curation, with a strong focus on analysis through programming (such as Python).
Here at Leeds, you’ll learn from leading researchers, with teaching expertise from the School of Geography, the School of Earth, Environment and Sustainability, and the Leeds Institute for Data Analytics (LIDA), a national institute for data science and AI.
By the end of the course, you’ll be equipped with the specialist knowledge and computational skills that are in demand across multiple industries. You’ll be able to develop creative, data-driven solutions that address real-world environmental challenges and the needs of society.
Why study at Leeds:
- Learn from data and AI experts: Your curriculum is directly influenced by the Leeds Institute for Data Analytics, whose active research grant portfolio comprises 155 projects supported by £120 million in external funding, and benefits from the University's partnership with the Alan Turing Institute. This means you will learn machine learning where leading research happens every day.
- Graduate with a real-world project: We’ve replaced the traditional academic dissertation with an applied, Environmental Data Science Project, meaning you’ll graduate with a practical notebook-style analysis that directly mirrors modern commercial workflows, alongside a report component.
- Guaranteed Industry Experience: Our two-week Global Industry Programme gives you experience of working on projects for UK and international organisations through a virtual consultancy experience. As well as giving you the opportunity to build key industry connections, you’ll also develop invaluable professional and practical skills that are highly valued by employers.
- No coding experience required: Over the course, you'll progress from foundational Python programming to advanced machine learning, developing the skills to apply data science with confidence.
- Develop in demand skills for future careers: You’ll build expertise in areas such as data science programming, machine learning, artificial intelligence and analysing large and complex datasets.
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Course details and modules
Master the complete end-to-end workflow of environmental data science. This programme moves beyond generic analytics, training you to navigate the specific complexities, noise, and nuances inherent in environmental datasets. You'll learn not just how to process information, but why and how it is collected in the field, ensuring your models form a reliable, accurate basis for environmental policy and commercial management.
The curriculum focuses heavily on the direct application of machine learning and data science to complex environmental and spatial challenges. You'll work with a multitude of diverse, real-world data types to build a breadth of experience, transitioning from historical data observation to predictive insight generation.
Starting with foundational programming and data handling, the course safely accelerates your capability, moving you toward the advanced, creative application of algorithms.
Upon completion, you'll possess a highly sought-after dual competency. By synthesising rigorous computational techniques with deep environmental intuition, you will be equipped to engineer sophisticated, data-driven solutions that directly inform high-level decision-making across multiple sectors.
Course structure
The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.
Compulsory modules
Programming for Spatial Data Science (15 credits)
Master foundational Python programming, focusing entirely on the unique challenges of spatial data. Designed for beginners, this module equips you to confidently manipulate spatial datasets, execute reproducible scientific analyses, and engineer clear data visualisations and maps. Beyond core syntax, you will adopt professional software development practices and navigate the ethical constraints of spatial data, grounding your technical execution in rigorous research standards.
Skills for Environmental Data Scientists (15 credits)
Secure the practical foundation required to manage complex environmental data projects. You will direct the initial stages of the data science workflow: structuring projects, designing robust sampling strategies, and extracting high-quality data from both academic and field sources. The module concludes with a residential field course in Cumbria, where you will physically deploy environmental sensors, troubleshoot hardware under real-world conditions, and collect your own primary datasets.
Data to Insights in Multiple Environments (15 credits)
Turn raw environmental data into strategic scientific insights. You will apply advanced analytical frameworks to diverse ecosystems, including deep-sea, freshwater, and agricultural environments. Using hands-on programming and statistical analysis, you will evaluate and select the precise data science techniques required to solve specific ecological and environmental challenges. By refining your critical thinking, you will tailor your approach to ensure your methodologies directly answer the unique scientific questions posed by each environment.
Data Science for Practical Applications (15 credits)
Accelerate your foundational expertise in core data science methodologies. You will execute data handling protocols, conduct exploratory data analysis, and build initial machine learning and visualisation models. Rather than studying abstract theory, you will directly manipulate diverse spatial and spatiotemporal datasets to solve tangible, real-world problems across multiple environmental contexts.
Creative Coding for Real World Problems (15 credits)
Push the boundaries of standard analytics by merging creativity with direct industry execution. Working in collaborative teams, you will deploy your expanding programming toolkit to engineer novel solutions for complex, real-world challenges set directly by external partners, giving you invaluable exposure to leading environmental organisations and prospective employers.
Deep Learning for Environmental Data (15 credits)
Bridge the gap between foundational machine learning and advanced deep learning architectures. Rather than simply deploying pre-built models, you will deconstruct the 'black box' of artificial intelligence to master the first principles of neural networks. Through practical labs, you will navigate real-world data constraints to engineer robust predictive models capable of solving complex environmental challenges.
Environmental Data Science Project (60 credits)
Move beyond the traditional academic dissertation by executing a real-world data science project. You will deliver your final submission as a deployable 'notebook' style analysis accompanied by a report, directly mirroring modern industry workflows. By synthesising your programming expertise and environmental intuition, you will generate robust insights and graduate with a tangible portfolio of reproducible code to clearly demonstrate your capabilities to future employers.
Optional modules
You’ll choose from a range of optional modules to tailor the course to your interests and career goals. Typical options include:
Digital Image Processing for Environmental Remote Sensing (15 credits)
Master the mechanics of Earth observation technologies. You will execute the fundamental principles of satellite and aircraft image acquisition, processing, and interpretation to extract critical environmental intelligence. Using industry-standard software, you will read, restore, enhance, and classify diverse remote sensing imagery, transforming raw geospatial data into actionable thematic outputs for real-world environmental research.
Environmental Assessment (15 credits)
Execute the rigorous principles of professional environmental assessment. You will deploy the exact tools used for global infrastructure and development planning, including Environmental Impact Assessments, Strategic Environmental Appraisal, and Multi-Criteria Appraisal. By bridging complex numerical modelling with public participation frameworks, you will generate the evidence required to support and influence high-level planning decisions.
Web-Based GIS (15 credits)
Engineer custom, dynamic web-based mapping applications. You will master industry-standard web development technologies for spatial data storage, manipulation, and visualisation, including HTML, JavaScript, CSS, and server-side database management systems. Through intensive coding tasks, you will build secure, efficient code and culminate your learning by developing a fully functional web-based GIS application from scratch.
Fieldwork
As part of the Skills for Environmental Data Scientists module, you will undertake a residential field course. Rather than relying solely on pre-cleaned secondary data, you will physically deploy environmental sensor networks, troubleshoot hardware in unpredictable conditions, and acquire your own primary datasets.
You may also choose to design and execute independent fieldwork in your final Environmental Data Science Project. By experiencing the friction and reality of physical data collection, you ensure your future computational models and insights remain rigorously grounded in real-world ecological contexts.
Learning and teaching
This programme immerses you directly in the professional data science workflow through a rigorous, problem-based learning approach. To ensure rapid skill acquisition, topics are delivered through a mix of lectures, seminars, and practical computer labs.
You will apply theoretical concepts to hands-on execution, engineering creative solutions to real-world environmental challenges using authentic datasets. By blending structured face-to-face instruction with advanced digital platforms to scaffold your learning, you will develop the technical agility and environmental expertise demanded by the modern sector.
Active research environment
You will be taught by an experienced team of academics tackling today’s most pressing environmental and data-driven challenges. Our staff are active members of several research groups, including the Institute of Spatial Data Science, River Basin Processes and Management, and Ecology and Global Change, as well as the Leeds Institute for Data Analytics (LIDA) and the Alan Turing Institute.
Specialist facilities
You'll have access to excellent teaching facilities within the School of Geography, including a GIS and Programming computer cluster with industry-standard software. If you choose to undertake a final Data Science Project that involves fieldwork and samples, the School is well equipped with scientific laboratories that have an extensive range of equipment to facilitate the preparation and analysis of water, soil and sediment samples.
Programme team
On this course, you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.
Assessment
Our assessment strategy is designed to mirror the demands of the modern environmental data sector. Rather than standard examinations, you will be evaluated on your ability to conduct in-depth data enquiries and engineer solutions to real-world environmental problems. Through a mix of individual analysis and group-based consultancy simulations, you will submit deployable code and translate your insights into professional deliverables, communicating your findings through executive summaries, reports, briefing documents, and panel presentations.
Applying
Entry requirements
A bachelor degree with a 2:1 (hons) in any subject, along with evidence of quantitative or computing skills.
We welcome ambitious graduates from a wide range of academic backgrounds who are interested in using data and technology to address environmental challenges.
We also encourage you to apply if you have a 2:2 (hons), relevant work experience or professional qualifications. We take a flexible and inclusive approach and consider every application on its individual merits.
International
We accept a range of international equivalent qualifications. For more information, please contact the Admissions Team.
English language requirements
IELTS 6.5 overall, with no less than 6.0 in any component. For other English qualifications, read English language equivalent qualifications.
Improve your English
International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.
This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Science (6 weeks) and Language for Science: General Science (10 weeks).
We also offer online pre-sessionals alongside our on-campus pre-sessionals. Find out more about our six week online pre-sessional and our 10 week online pre-sessional.
You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.
How to apply
Please visit our How to Apply page for full details of the application process and the supporting documents required as part of your application.
We encourage all applicants to apply as early as possible.
Application deadlines
- International applicants: Friday 30 July 2027
- UK applicants: Friday 10 September 2027
To apply, click the button below to access the University’s online application system.
International applicants can find further information on visas, immigration requirements and student support on our International students pages. We recommend applying as early as possible to allow sufficient time for visa processing before your programme starts.
Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.
Admissions policy
University of Leeds Admissions Policy 2027
This course is taught by
Contact us
School of Geography Postgraduate Admissions Team
Email: geo-tpg-enq@leeds.ac.uk
Fees
UK: £14,700 (Total)
International: £33,500 (Total)
Read more about paying fees and charges.
For fees information for international taught postgraduate students, read Masters fees.
Additional cost information
Standard travel, subsistence and accommodation costs associated with compulsory field trips are covered by the University. However, you must pay for incidental or personal expenses such as suitable clothing and footwear.
There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more on our living costs and budgeting page.
Scholarships and financial support
If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government. Learn more about Masters funding.
Scholarships are also available to help fund your Masters. Find out more and check your eligibility below:
Career opportunities
Employers increasingly demand professionals who can bridge the gap between data science, machine learning, and environmental science. By mastering this specific environmental context, you are perfectly positioned for specialised, high-impact roles within climate tech startups, environmental consultancies, government agencies, and the renewable energy sector.
Your skills won’t be limited to the environmental sector. The advanced Python programming, machine learning, and spatial data skills you develop are highly transferable and are well-suited to roles in data science in sectors such as finance, logistics, and telecommunications both in the UK and internationally.
Example job titles include:
- Environmental Data Scientist
- Data Scientist / Data Analyst
- Climate or Sustainability Analyst
- Machine Learning Engineer
- Geospatial Ecologist/Data Scientist
- Climate/Biodiversity Informatics Specialist
- Biophysical Modeller
- Environmental Consultant
- Remote Sensing Analyst
- Policy or Research Analyst
Studying at Leeds also gives your degree strong employer recognition. The University of Leeds is consistently one of the most targeted universities by leading graduate employers, helping you stand out in a competitive job market.
Careers support
At Leeds, we help you to prepare for your future from day one - that’s one of the reasons Leeds graduates are so sought after by employers. The University’s Careers Centre is one of the largest in the country, providing a wide range of resources to ensure you are prepared to take your next steps after graduation and get you where you want to be.
- Dedicated Employability Officer - gain quality advice, guidance and information to help you choose a career path. From CV and cover letter writing to supporting you with job applications, our School’s dedicated Employability Enhancement Officer is on hand to help maximise your capabilities through a process of personal development and career planning.
- Employability and networking events - we run a full range of events, including careers fairs in specialist areas and across broader industries, with employers who are actively recruiting for roles, giving you the opportunity to network with industry sponsors.
- Employability skills training - we help you build the skills employers really value. Throughout the course, you’ll develop key transferable skills such as communication, teamwork and problem solving, helping you feel confident and work‑ready when you graduate.
- MyCareer system - on your course and after you graduate, you’ll have access to a dedicated careers portal where you can book appointments with our team, get information on careers and see job vacancies and upcoming events.
- Joblink - a student job shop offered by our Leeds University Union (LUU), designed to link students with local employers who provide rewarding work experience. LUU also offers volunteering opportunities and over 300 clubs and societies to get involved in.
Find out more at the Careers website.
As a Masters student at Leeds, you’ll have the unique opportunity to gain real-world industry experience with our Global Industry Programme.
You’ll develop key professional skills and gain invaluable insight into working in your chosen field, helping to solve a real business problem from a live company brief.
This experience will enhance your CV, helping you stand out in the competitive graduate jobs market and improving your chances of securing the career you want.
Benefits of the Global Industry Programme:
- Fully online and designed to fit around your studies.
- Opportunities to make professional networks in areas such as digital marketing, business growth, sustainability and funding strategy.
- Gain valuable insight and build consultancy experience with a UK or international organisation, working on a time limited brief.
- Work as part of a team across disciplines to tackle real business needs.
- Advance your experience and hands-on skills by putting the course teachings into practice.
- Improve your employability prospects.
- Make new friends, build confidence and consider your future plans.