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urbandatascience

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Course materials for Urban Data Science at UCLA

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# Urban Data Science

**Course website:** This repository contains the Jupyter notebooks for the video lectures and the in-class exercises.
See the course videos, readings, and other materials at https://urbandatascience.its.ucla.edu.

**Instructor:** [Adam Millard-Ball](https://millardball.its.ucla.edu), he/him

**About this course:** New data sources are a potential goldmine for urban planners and policy makers. But sometimes they are large, sometimes they are messy, sometimes they are awkward to access, and often they are all of these things. In this hands-on course, we’ll develop skills in scraping, processing, and managing urban data, and using tools such as natural language processing, geospatial analysis, and machine learning. We’ll use examples from transit, housing, and equity planning, and build competence in open-source tools and languages such as Python and SQL. We’ll also consider the limits to data science, and the biases and pitfalls that "big data" can entail.

**Prerequisites:** Basic Python programming experience. You should be familiar with Python syntax, Jupyter notebooks, plotting via `matplotlib`, and `pandas` dataframes.

# Modules

1. [APIs](https://github.com/UCLALuskin/urbandatascience/tree/main/lectures/1%20APIs)
2. [Scraping](https://github.com/UCLALuskin/urbandatascience/tree/main/lectures/2%20Scraping)
3. [Wrangling](https://github.com/UCLALuskin/urbandatascience/tree/main/lectures/3%20Wrangling)
4. [Spatial relations](https://github.com/UCLALuskin/urbandatascience/tree/main/lectures/4%20Spatial%20relations)
5. [Classification part 1](https://github.com/UCLALuskin/urbandatascience/tree/main/lectures/5%20Classification%20part%201)
6. [Classification part 2](https://github.com/UCLALuskin/urbandatascience/tree/main/lectures/6%20Classification%20part%202)
7. [Clustering](https://github.com/UCLALuskin/urbandatascience/tree/main/lectures/7%20Clustering)
8. [Parsing text](https://github.com/UCLALuskin/urbandatascience/tree/main/lectures/8%20Parsing%20text)
9. [Natural language processing](https://github.com/UCLALuskin/urbandatascience/tree/main/lectures/9%20Natural%20language%20processing)
10. [Big data](https://github.com/UCLALuskin/urbandatascience/tree/main/lectures/10%20Big%20data)

[In-class exercises](https://github.com/UCLALuskin/urbandatascience/tree/main/classes)

**For more information:** [Visit the course website](https://urbandatascience.its.ucla.edu)

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