COURSE CURRICULUM

The MSc in Data Science for Environmental Science is a one-year, full-time program designed for students and professionals seeking to apply data science techniques to real-world environmental challenges. The course blends theory with hands-on practice, offering around 15 hours of weekly contact through lectures, labs, and seminars, alongside approximately 25 hours of independent study. Students develop skills in Python programming, data mining, and statistical modelling using tools like R. The program emphasizes applying these techniques to environmental data, such as climate models, geophysics, or big data from ecological monitoring systems.A major component of the course is the dissertation, which involves an independent research project using data science methods to investigate an environmental topic. Students work under academic supervision and can choose topics ranging from weather patterns and climate change to ocean modelling and environmental monitoring. This project allows students to apply their technical skills in Python and R to analyse complex datasets, generate insights, and contribute to the understanding of environmental systems.The course includes modules on professional development, equipping students with key communication, presentation, and project management skills essential in scientific careers. Additionally, students explore ethical and societal issues in computing, gaining a broad understanding of the impact of data science on policy and the environment. By the end of the program, graduates are prepared for roles in academia, government, or industry, with a strong foundation in data analysis, environmental science, and research methodologies. The skills gained also serve as a strong platform for further doctoral study in environmental data science.