Master of Data Science for Public Policy   Master of International Affairs   Master of Public Policy  

Geospatial analysis for data science

From election results over housing prices to air pollution measurements – most data can be located on a map and can thus be considered geodata. This course covers the basics of geospatial analysis and its application in real-world data science problems with a focus on public policy-related topics. We will start with the basics of geospatial data, such as the fundamental data models vector and raster, typical data formats, and (open) data sources. Different tools to manage, analyse, edit and visualise geodata will be introduced, including QGIS and respective R and Python packages. Then, we will delve into spatial data operations as well as different techniques for spatial statistics that will provide the tools to accomplish geodata-based use cases. Finally, we will cover the topic of data privacy for location data.
In summary, this course will enable the students to use tools for handling geodata, extract insights through suitable operations and spatial statistics methods, and create powerful visualisations with maps.

This course is for 2nd year MIA, MPP and MDS students only.

Instructor

  • Lynn Kaack , Assistant Professor of Computer Science and Public Policy