You’ll learn data science methods from the ground up while gaining a broad understanding of ecological theory. Built on foundational training in R and Python programming languages, you’ll layer in skills in sampling design and biodiversity monitoring methods — including bioacoustics, camera traps, remote sensing, and eDNA — along with 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, you’ll also learn from academics across Robotics, Connected Environments and Geography, with added input and research opportunities from the Zoological Society of London and the Natural History Museum, along with industry partners.
Throughout the course, you’ll apply your skills through field studies, in-depth problem-based group work, and an extensive data-science dissertation project. You’ll graduate ready to lead the next generation of AI-equipped environmental scientists, working to solve the critical ecological challenges of our time.
There is a rapidly growing demand for scientists who can work across the full pipeline of environmental data science, from understanding and deploying the cutting-edge sensors that capture ecological data to the statistical and computational tools that turn raw data into ecological insight.
With this multidisciplinary skill set, project management skills, in-depth knowledge, and practical experience of fieldwork and independent research, you’ll be ready to join the next generation of data-savvy biologists driving progress in this time-critical field.
This master’s provides a unique skill set covering data science, environmental sampling tools and techniques, and biodiversity inference — a rare and highly valued combination that will prepare you for a meaningful career in data-driven decision making.
You’ll be equipped to work in any organisation that uses — or wants to use — data science to tackle environmental or social challenges, including environmental, restoration, or conservation groups, NGOs, tech companies and start-ups, local or central government agencies, museums, and engineering firms. Some students go on to specialise further by pursuing a PhD in either data science or ecology.
Graduates have found positions in universities in the UK and around the world. Others have found careers in the humanities, the sciences, software development, and other related fields.*
Graduate Outcomes survey carried out by the Higher Education Statistics Agency (HESA), looking at the destinations of graduates from 2021 to 2024.