COURSE CURRICULUM

The MSc Data Science (Social Analytics) program provides advanced training in statistical analysis, computational methods, and data-driven approaches to understanding social phenomena. Core modules, including Statistics and Machine Learning 1: Statistical Foundations and Statistics and Machine Learning 2: AI, Complex Data, Computationally Intensive Statistics, develop strong analytical and computational skills for handling complex datasets. Understanding Databases and Understanding Data and their Environment equip students with essential expertise in data organisation, management, and contextual interpretation, while Applying Data Science focuses on practical applications, enabling students to translate data insights into actionable solutions. The Extended Research Project allows students to undertake an independent, supervised study, integrating technical, analytical, and social science methods to address real-world social challenges. Optional modules, such as Topological Data Analysis, Privacy, Confidentiality and Disclosure Control, Digital Planning - Spatial and Policy Analysis, and Social Network Analysis: Concepts and Measures, allow students to specialise in advanced computational techniques, policy analytics, spatial data, and network-based social research. The program fosters interdisciplinary collaboration, critical thinking, and professional skills, including problem-solving, communication, and teamwork. Graduates are equipped for careers in policy, research, consultancy, business, and other sectors requiring expertise in social data analytics, combining technical competence with an understanding of societal dynamics to address complex local and global challenges.