We will explore the intersection of urban analytics and sustainable development. It is a 30-credit course designed to give you the necessary skills to process, analyse and visualise data at a fine-grained scale using Python, the most popular programming language in the field of spatial data science.
This course focuses on sustainable urban development and includes advanced libraries for spatial analysis and methods to link and recreate fine-scale data. By the end of this module, you will get a strong foundation in Python and geospatial data analysis tools to address urban challenges.
This module assumes that you are already familiar with geospatial data, data formats (vector and raster), and the basics of Python. Even though the module covers a short introduction to recall the most relevant concepts, it has the following modules as prerequisites: GG1001, GG2011 and GG3209.
This course focuses on sustainable urban development and includes advanced libraries for spatial analysis and methods to link and recreate fine-scale data. By the end of this module, you will get a strong foundation in Python and geospatial data analysis tools to address urban challenges.
This module assumes that you are already familiar with geospatial data, data formats (vector and raster), and the basics of Python. Even though the module covers a short introduction to recall the most relevant concepts, it has the following modules as prerequisites: GG1001, GG2011 and GG3209.
Course Type: 2023-2024 Modules
Shared Course: No
Feeder Course: No