URBN PL 213Urban Data Science
Urban Planning · 4 units · Graduate courses (200-299)
New data sources are potential goldmine for urban planners and policy makers. But sometimes they are large, messy, or awkward to access, and often they are all of these things. Development of skills in scraping, processing, and managing urban data, and using tools such as natural language processing, geospatial analysis, and machine learning. Use of examples from transit, housing, and equity planning, and building of competence in open-source tools and languages such as Python and SQL. Consideration also of limits to data science, and biases and pitfalls that big data can entail.
Letter grading.
When it runs
Not on the schedule for any of Fall 2025 through Spring 2027. UCLA publishes only that window, so this does not mean the course is gone — check the official listing.
Requisites
Official UCLA wording
Preparation: basic Python programming experience or introductory Python course.
BruinTree reads · Preparation
needs reviewconfidence 0.00 · from textBruinTree could not read this requirement — see UCLA’s wording above.
- · could not read "basic Python programming experience" (no course number found)
- · could not read "introductory Python course" (no course number found)
- · no course reference could be read from this requisite
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
Nothing — this is an entry point.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.