Introduction to Urban Data Science 2019

Course description

In this course, attendees will be provided with an overview perspective on location-based technologies with a focus on urban applications. From human mobility models and theory to neighborhood detection and finding an appropriate location for placing a shop or amenity attendees will be introduced to the mechanics and building blocks of a number of research works with a strong application orientation. Historically important theoretical concepts in the area will be covered that include Central Place Theory and Reilly’s law of retail gravitation. Next, the spotlight will be put on newer advancements in the area of the so-call gig economy, introducing services like Uber and Airbnb, highlighting opportunities for research using corresponding transport and hospitality datasets.

Course tools

Python, Scipy, Scikit-Learn, Networkx.

About the lecturer

Dr. Anastasios Noulas

Fields of interests: Location-based Technologies, Human Mobility, Urban Data Science