12 monthsProgramme duration
44,400 GBPTuition Fee/year
25 Jun, 2027Application Deadline
SepStarting Month
Programme overview
Main Subject
Biological Sciences
Degree
MSc
Study Level
Master's
Study Mode
On Campus
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.
Programme overview
Main Subject
Biological Sciences
Degree
MSc
Study Level
Master's
Study Mode
On Campus
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.
Admission Requirements
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