COURSE CURRICULUM

The Environmental Data Analytics MSc is structured around a set of modules that combine environmental science with advanced data and digital skills. Spheres of the Environment and Climate Change Adaptation provides a foundation in environmental systems, examining interactions between the atmosphere, biosphere, hydrosphere, and geosphere, alongside strategies for adapting to climate change. Environmental GIS and Remote Sensing Applications focuses on spatial analysis techniques, enabling students to use geospatial data, satellite imagery, and mapping tools to investigate environmental patterns and processes. Programming and Machine Learning develops core computational skills, introducing programming techniques and machine learning methods for analysing complex environmental datasets. The DBMS, Big Data and Communication for Data Scientists module explores database management systems, big data technologies, and effective communication of analytical findings to technical and non-technical audiences. The program also offers a Master’s with professional placement, providing valuable industry experience and the opportunity to apply academic knowledge in real-world environmental or data-driven roles. The Research Project allows students to conduct an independent, in-depth investigation into a chosen environmental analytics topic, developing advanced research, data analysis, and problem-solving skills while producing a substantial piece of postgraduate-level work relevant to climate, sustainability, and environmental decision-making.