What's Next?
This course only scratches the surface of many of the topics. The aim is to provide you with the foundation so that you can continue to deepen your skills on your own.
Here are some recommended resources. Please contact us if you have other suggestions to add to the list.
General coding
- Data Carpentry offers many online course materials on Python, R, and git
- Ozan Jaquette’s Introduction to Programming and Data Management course [a good introduction to R]
Spatial analysis
- Michael Szell’s Geospatial Data Science course
- Geoff Boeing’s Advanced Urban Analytics course [more of a focus on network and spatial analysis than we cover here]
Databases and SQL
- PostGIS in Action [ebook available through the UCLA library]
- Software Carpentry, Databases and SQL
- Coursera, Learn SQL Basics for Data Science [you can audit for free]
Web scraping
Machine learning
