COURSE CURRICULUM

The MSc in Data Science for Environmental Sustainability provides students with the skills and knowledge to tackle pressing environmental challenges using advanced data science techniques. In the first year, core modules equip students with a strong foundation in big data, machine learning, and artificial intelligence, and how these tools can be applied to environmental sustainability. Modules in applied computing for environmental contexts teach students to handle and analyse complex environmental datasets, while courses on policies, principles, and practice of environmental sustainability, as well as business and the environment, provide essential context for informed decision-making. The dissertation allows students to undertake a substantial, independent research project applying data science methods to real-world sustainability issues, integrating both practical and theoretical learning. Optional modules offer opportunities to specialise further, with subjects including data visualisation, water management, climate change adaptation and resilience, remote sensing of hazards, and numerical modelling of environmental hazard processes. Through a combination of hands-on projects, applied computing skills, and theoretical understanding, students develop expertise in data analysis, visualisation, and interpretation within environmental contexts. Graduates are prepared for careers in environmental consultancy, policy-making, sustainability-focused industries, and research, and are equipped to design, analyse, and implement data-driven strategies to address global sustainability challenges and promote climate resilience.