This course invites students to rethink traditional spatial analysis and geocomputational methods as well as to investigate and apply new concepts and methods offered by spatial data science to leverage the use of different types of geographic information to tackle real-world problems. This course focuses on theoretical discussions on relevant topics and methods used in spatial data science, as well as on applying a range of spatial data science skills and tools to solve real-world problems and model geographic phenomena. Students will read, discuss and synthesize research articles, and develop coding solutions for spatial data science tasks. No prior coding experience is required for this course, but two soft skills are a must to succeed: 1. the ability to move past debugging frustrations and work independently to find solutions, and 2. a collaborative attitude towards work.
Analytical Approaches in Spatial Data Science