COURSE CURRICULUM

The Artificial Intelligence for Science MSc equips students with advanced skills to apply AI and machine learning techniques to scientific research and problem-solving. Core modules provide a comprehensive foundation, including AI and Machine Learning for Science: From Theory to Application, AI-Augmented Scientific Discovery: Frontiers and Issues, Data Analysis and Visualisation, Ethics of Artificial Intelligence and Contemporary Technology, and a Research Project in AI for Science. These modules develop expertise in designing and implementing AI methods, integrating computational approaches with scientific inquiry, and critically evaluating the ethical and societal implications of AI technologies. Optional modules allow students to tailor their learning to specific research interests. In one optional group, students can choose from Time Series, Neural Dynamics and Computation, or AI Applications in Biosciences, providing practical applications of AI in various scientific domains. In a second optional group, students select from Bayesian Statistics and Computational Methods, Advanced Statistical Methods for Psychologists, or Neurocognitive Modelling, enhancing their analytical and modelling capabilities. The program emphasises hands-on, research-led learning, enabling students to apply theoretical knowledge to complex scientific challenges. Graduates develop the technical, analytical, and professional skills necessary for careers in research, data science, computational modelling, or further postgraduate study, making significant contributions to interdisciplinary scientific and AI-driven projects.