Social Networks in Economic Geography and Spatial Machine Learning 2400-ZEWW951
The main aim of the course is to make students familiar with the broad variety of data science methods for spatial data – the analysis of spatial networks and spatial machine learning. Course is divided into two parts. The first one will be conducted by a visiting scholar: prof Balázs Lengyel and the other will be conducted by prof. Katarzyna Kopczewska and mgr Maria Kubara.
The course will be coordinated by an onsite lecturer – mgr Maria Kubara, while the whole class material will be delivered by the visiting professor.
The course will be taught in an intensive workshop setting over the course of two weeks between 17 and 28 February 2025. The students are asked to bring their own laptops with R v.3.3.0+ and RStudio Desktop installed in order to take active part in the practical live code exercises discussed during the class.
Type of course
Course coordinators
Learning outcomes
After this course the student:
- is familiar with the challenges of spatial data operation
- knows a range of machine learning techniques and can apply it to the spatial data in R
- student knows the practices of network analysis
- student knows the necessary tools and coding approaches to appropriately handle spatial data and spatial networks
Assessment criteria
The final grade will be based on the exam / project result.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: