The big data revolution is erupting in the smart city discussion (Grimaldi, Fernandez, & Carrasco, 2018). After 2010’s, we moved from a relative data scarcity to an unprecedented deluge of data (Talia, Trunfio, & Marozzo, 2015) that provides wider, finer-grained and real-time information of what is occurring in all the dimensions of the city: business, retail, housing, social, environmental, telecommunication, etc. Different types of databases have been generated in the last 20 years concerning the conditions of living, the built environment or the daily activities that take place in the city. Their ownership are either public or private (“open-data” policy, banking, telecommunication, retail transactions, etc.) (Manyika, 2011). Their sources are divided into two categories: automated and volunteered. Automated data are collected by intelligent systems such as connected sensors, CCTV, finger-prints, iris scans etc. Volunteered data are offered by users by formal consent. They can be generated by traditional forms and web-based formularies or massively collected through social channels (Davenport & Harris, 2007). Practitioners and scientists look for new applications that can make the citizens’ life better improving the services provided to them such as mobility, energy, housing or job seeking. Complexity science, Complex networks theory are fashioning new models of urban services (Grimaldi et al., 2018). Foth et al. (2011) add the creation of a new scientific field is emerging that they name “urban informatics”. They believe the potential promises are not only to give sense to cities as they are currently shaped (by identifying patterns or models or laws) but also to simulate and predict future possible scenarios. In our course, after a presentation of the different concepts of Smart City, Sustainable City, Data-driven city, we present few applications that Big Data offers to the urban managers.