The analysis of geographic information, such as those describing human movements, is crucial due to its impact on several aspects of our society, such as disease spreading (e.g., the COVID-19 pandemic), urban planning, estimation of well-being, pollution, CO2 emissions, and more.

This course teaches the fundamental concepts and techniques underlying the analysis of geographic and mobility data, presenting data sources (e.g., mobile phone records, GPS traces, geotagged social media posts), data preprocessing techniques, statistical patterns, mobility laws, predicting and generative algorithms, and real-world applications (e.g., diffusion of epidemics, socio-demographics, link prediction in social networks). The course also provides a practical perspective through the use of advanced geoanalytics Python libraries.

Prerequisites: Python (pandas, scikit-learn), Databases, Data Mining, Social Network Analysis