COURSE CURRICULUM

The MSc in Data Science and Analytics is a one-year interdisciplinary program designed to provide students with both theoretical understanding and practical skills in handling and analysing complex datasets. Delivered by the School of Mathematics in collaboration with the School of Computer Science and Informatics under the Data Science Academy, the course equips students with advanced capabilities in data processing, statistical analysis, and computational modelling to support effective decision-making across sectors. The core curriculum includes Applied Machine Learning, Computational Data Science, Foundations of Operational Research and Analytics, and Foundations of Statistics and Data Science. These modules provide a strong base in key analytical and machine learning techniques, as well as the theoretical tools needed to work with big data. The course culminates in a substantial 60-credit dissertation, allowing students to apply their knowledge to a focused research or practical project.In addition to the core modules, a wide range of optional modules enables students to tailor the program to their interests and career goals. Options include Distributed and Cloud Computing, Data Visualisation, Databases and Modelling, and Human Centric Computing, which offer insight into technological and user-focused applications. For those interested in applying data science to real-world problems, modules such as Statistics and Operational Research in Government, Healthcare Modelling, Time Series, and Statistical Programming with R and Shiny provide sector-specific skills. Modules like Stochastic Search and Optimisation and Mathematical Methods for Data Mining delve deeper into the mathematical and computational methods underpinning modern data science. This blend of core and optional content ensures graduates are well prepared for roles in data-intensive industries or research. With a balance of practical experience and theoretical grounding, the program develops the analytical thinking, programming proficiency, and problem-solving skills essential for success in today’s data-driven world.