This module offers an exciting introduction to the field of computational social science, where data science meets the study of human behaviour and societal change. Whether you are a human geographer exploring spatial dynamics or a computer scientist looking to apply cutting-edge methods to study societal challenges, this module equips you with practical skills and expertise to analyse data and solve problems across a range of social science topics, including population dynamics, human mobility or demographics. Through a series of hands-on computational activities, you will discover how to extract insights from complex datasets using a variety of advanced data science and machine learning techniques. The module emphasises practice over theory, including applications of supervised and unsupervised machine learning algorithms for classification, clustering and natural language processing (NLP), as well as other data science tools such as network analysis or time series modelling. The module highlights the potential of novel data sources, particularly those derived from digital traces, to address social science questions with unprecedented depth. Additionally, you will be encouraged to critically reflect on the ethical considerations and societal impacts of leveraging such data and employing computational approaches.