Program Overview

Introduction to the Ecology and Data Science MSc

The Ecology and Data Science MSc is a one-year program designed to address critical global environmental challenges by equipping students with a sought-after skill set spanning data science and ecology. This interdisciplinary master's program draws on expertise from across University College London (UCL), the Institute of Zoology, and the Natural History Museum.

About the Program

Students will learn data science methods from the ground up while gaining a broad understanding of ecological theory. The program combines skills in sampling design, biodiversity monitoring methods, sensor design, statistical programming languages like R and Python, and the most up-to-date machine learning and AI tools, including deep learning and computer vision. Rooted in UCL's Department of Genetics, Evolution and Environment and housed in the People and Nature Lab at UCL East, students will also learn from academics across Robotics, Connected Environments, and Geography, with added input and project opportunities from the Zoological Society of London and the Natural History Museum, plus other industry partners.

Who This Course Is For

This program is for ecologists who want to learn technological and computational skills and for data scientists who want to develop their skills and apply them to critical environmental issues. It is relevant to conservation-focused or data science careers across government, Non-Governmental Organisations (NGOs), charities, the private sector, and academia.

What the Course Will Give You

The Ecology and Data Science MSc has been developed to address the pressing need for ecologists who can harness ever-evolving computational power and AI tools to monitor, manage, and conserve precious ecosystems and wildlife populations. By joining this highly popular one-year program, students will build a full-stack toolkit to implement the whole lifecycle of ecological analysis. Benefits include:

• Studying in UCL's People and Nature Lab at the Queen Elizabeth Olympic Park, part of the Centre for Biodiversity and Environment Research.
• Developing expertise in the latest tools and technologies in sampling design, monitoring, sensor design, statistical programming, machine learning, and deep learning.
• Gaining real-world experience through collaborations with the Natural History Museum and the Zoological Society of London, and project opportunities with industry partners.
• Planning and conducting extensive independent research and developing skills to report findings to various audiences.
• Building the program around aspects of ecology and data science that most interest the student, with optional specialisms in areas like behavioral ecology, science communication, and nature-friendly urban design.
• Gaining hands-on experience through a week-long field project in Queen Elizabeth Olympic Park.
• Leaving well-equipped to apply a sought-after mix of skills and expertise to conservation-based or data science careers.

The Foundation of Your Career

This master's will give students a broad knowledge base and specialist skill set across both ecological science and data science, a rare and highly valued combination for a meaningful career. Students will be equipped to work in any organization that uses or wants to use data science to tackle environmental or social challenges, including environmental, restoration, or conservation groups, NGOs, tech companies, start-ups, local or central government agencies, museums, and engineering firms. Some students may go on to specialize further by pursuing a PhD in either data science or ecology.

Employability

There is a rapidly growing demand for scientists with expertise in cutting-edge technological, statistical, and computational tools to solve ecological challenges. With a multidisciplinary skill set, project management skills, in-depth knowledge, and practical experience of fieldwork and independent research, students will be ready to join the next generation of data-savvy biologists driving progress in this time-critical field.

Networking Opportunities

Students will have regular opportunities to connect, collaborate, and build professional contacts as part of their master's. This includes networking with students and academics from within and beyond the faculty at divisional, departmental, and other research seminars, participating in seminar series at the Natural History Museum and the Zoological Society of London, and joining regular social events organized by and within the partner institutions. Students will also work and network with industry professionals involved in the Nature-Smart Challenge module, from environmental consultancies, wildlife NGOs, local community groups, and local government, and participate in careers events through UCL Careers during the academic year to enhance their CV writing and interview skills.

Teaching and Learning

Students will learn through a broad suite of teaching approaches, including lectures, seminars incorporating problem-based learning, group discussions, concept mapping, task-focused workshops, hands-on experience, and reflective learning. Assessment will be through a variety of both formative and summative approaches, including case study reports, individual video presentations, group presentations/pitches, grant proposals, reflective summaries, science communication, and a final research project developed in collaboration with UCL academics and/or with a program partner. The program includes approximately 300 contact hours with approximately 1200 hours of self-directed learning.

Modules

The program consists of compulsory and optional modules. Compulsory modules include:

• Computational Methods in Biodiversity Research
• Foundations in Ecology and Ecological Monitoring
• Technology for Nature
• AI for the Environment
• Nature-Smart Challenge: Data Science
• MSc Ecology and Data Science Research Project

Optional modules may include:

• Behavioural Ecology for the Anthropocene
• Science Communications for Biologists
• Biodiversity Generation and Maintenance
• Foundations of Citizen Science
• Foundations of Nature and Climate-Friendly Urban Design
• Biodiversity dynamics on a changing planet

Fieldwork

There is a one-week fieldwork course in Term 1, which takes place in the Queen Elizabeth Olympic Park where the UCL East campus is based. Students will spend a significant amount of time outdoors and should be prepared with suitable weather-proof clothing, sturdy shoes, and Wellington boots.

Accessibility

The department will endeavor to make reasonable adjustments for students with disabilities. Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information can also be obtained from the UCL Student Support and Wellbeing Services team.

Fees and Funding

Fees for This Course

• UK students: ｣25,300 (full-time), ｣12,650 (part-time) for the 2026/27 academic year.
• International students: ｣42,700 (full-time), ｣21,350 (part-time) for the 2026/27 academic year.

Additional Costs

• A fee deposit will be charged at 2.5% of the first year's fee for UK students and 10% for international students.
• Students are required to have a laptop suitable for running R software.
• Depending on the options chosen or where the project is conducted, students may need to travel to Bloomsbury, South Kensington, or Regent's Park.
• The cost of a monthly 18+ Oyster travel card for zones 1-2 is approximately ｣119.90.

Funding Your Studies

The UCL East Scholarship is available to support the ambitions of east Londoners by funding the fees and living costs of eligible Master's programs, including this MSc at UCL. Further details on scholarships and funding opportunities relevant to nationality can be found on the UCL Scholarships and Funding website.

Next Steps

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding, particularly overseas applicants, should take note of application deadlines. There is an application processing fee for this course of ｣90 for online applications. When assessing applications, the admissions team would like to learn about the applicant's reasons for studying Ecology and Data Science at graduate level, why they want to study at UCL, what attracts them to the program, how their background meets the program's demands, and their professional aspirations with the degree. The personal statement is an opportunity to illustrate whether the applicant's reasons for applying match what the program will deliver.