Introduction to Urban Data Science
CRP and DESIGN 4680/5680
2:45 pm - 4:00 pm
Taught by Wenfei Xu
306 Sibley Hall
Students must also enroll in:
Practioners' Talk Series
4:30 pm - 5:30 pm
101 Sibley Hall
1) the set of data analysis tools and methods used to understand a wide array of big data and big spatial data sources and, 2) questions of urban development, structure, complexity, theory, policy, dynamics, and outcomes.
These approaches enable more spatiotemporally dynamic and granular analyses of cities and allow researchers new insight into urban dynamics.
This course will provide a toolkit to speak through data, code, statistics, and visualization. Using open-source data and computational tools in Python and the Jupyter Notebook environment, we will learn how to design testable research questions, collect and prepare data, apply relevant analytical techniques, present our process and results in an engaging and informative way, and identify the limitations of quantitative analysis. A personal laptop will be required.
Along with the course, students are required to enroll in the public series Practitioner Talk Series.
Gaussian kernel function. Zhan, C., Han, J., Hu, S., Liu, L., & Dong, Y. (2018). Spatial downscaling of GPM annual and monthly precipitation using regression-based algorithms in a mountainous area. Advances in Meteorology, 2018, 1-13.