COURSE CURRICULUM

The MSc Data Science (Earth and Environmental Analytics) program combines advanced data science techniques with environmental and earth system applications, equipping students with the skills to analyse and interpret complex datasets in a range of contexts. Core modules such as Statistics and Machine Learning 1: Statistical Foundations and Statistics and Machine Learning 2: AI, Complex Data, Computationally Intensive Statistics provide a strong grounding in analytical, computational, and machine learning techniques. Understanding Databases and Understanding Data and their Environment develop essential skills in data organisation, management, and contextual interpretation, while Applying Data Science allows students to apply these methods to real-world environmental challenges. The Extended Research Project offers an opportunity for independent, supervised research, integrating technical and domain knowledge to address pressing issues such as climate change, natural hazards, and conservation. Optional modules, including Privacy, Confidentiality and Disclosure Control, Measuring and Predicting 2, Computational Subsurface Geoscience, and Key Interpretation Skills, enable students to tailor their studies toward areas such as environmental prediction, geoscience modelling, and data privacy. The program fosters interdisciplinary collaboration and professional skills in problem-solving, communication, and project management, preparing graduates for careers in environmental management, research, policy, consultancy, and other data-driven roles. It equips students to apply data science effectively to complex environmental and earth system challenges.