pitmonticone / geospatial_course_unitn

repository with code and documentation for the course "Geospatial analysis and representation for data science" for the students in data science of the university of Trento

Geospatial analysis and representation for data science

repository with code and documentation for the course "Geospatial analysis and representation for data science" for the students in Data Science of the University of Trento

web site with the content of the course - https://napo.github.io/geospatial_course_unitn/

Course information

Description

The laboratory aims to provide the necessary basis for learning how to manage, analyze and visualize geospatial data through open source tools (geospatial libraries for python, qgis, R …)

At the end of the course, students will be able to:

• understand the specificity of the geospatial data model
• elaborate and integrate geospatial data (vector and raster)
• create maps (also accessible via the web)

Teaching Method

the teaching method chosen is "hands-on learning": at each lesson some geospatial analysis concepts are introduced showing python code (with Jupyter Notebook) on the fly.
Step by step students put the concepts into practice and also face everyday problems in data analysis.
At the end of each lesson an exercise is proposed to reinforce what has been learned.
In the next lesson the solution is then presented, thus repeating the concepts exposed and inserting something new.

Teachers

• Diego Giulani
• Maurizio Napolitano

Lessons

Maurizio Napolitano
every Friday from 1 October to 3 December - room 12 Department of Sociology and Social Research - University of Trento

MyBinder

Slide about the course

view the slides - download

Course websites

• official page of the University of Trento
• Lessons by Maurizio Napolitano
• Github with code and other resources by Maurizio Napolitano

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License of the materials

• slides and texts under CC-BY
• code under MIT License