Data Analytics and Visualization
RE 519, Runstad Department of Real Estate, University of Washington, Autumn 2025
Monday & Wednesday, 2:30 - 3:50pm, Mechanical Engineering Building 245
The primary objective of this course is to familiarize planning students with methods and techniques they are likely to encounter and use in planning departments and organizations. Planners must be quite versatile, in that they must be knowledgeable of a variety of analytical methods, including statistical analysis and techniques, demographic techniques; economic analysis, project planning techniques, geographical and spatial analysis techniques and analysis, and various forms of transportation analysis.
Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics. Nathan Yau. 2024.
Data Visualization: A Practical Introduction. Kieran Healy. 2019.
Schedules
Go to the recent section. This schedule is subject to change and please check back regularly for updates. All readings and materials can be directly accessed via the links below, although some may require a UW NetID login.
Module 1 - Introduction to Data Science
- Sep 24
- Overview, Values of Data Science, Statistics Review I
- Slides
- LAB 1-AR and Python Setup
- OptionalVisual and Statistical Thinking: Displays of Evidence for Making Decisions. Edward Tufte. 1997.
- OptionalSeeing Theory - A Visual Introduction to Probability and Statistics. Daniel Kunin.
- Sep 26
- Optional Intro to Git and GitHub
- Online Session at 1:00 - 2:00 pm via Zoom
- Sep 29
- Data Type and Sources
- Slides
- LAB 1-BBasic of Python/R and Markdown
- Oct 01
- Data Science Pipeline and Tools
- Slides
- LAB 1-CDownload and Play with Data
Module 2 - Prepare and Explore Data
- Oct 06
- Data Manipulation 1
- Slides
- LAB 2-AData Wrangling and Packages for Dataframes
- LAB 1 DUE
- Oct 08
- Data Manipulation 2
- Slides
- LAB 2-BData Wrangling and Packages for Dataframes
- Oct 10
- Optional Webscraping
- Online Session at 1:00 - 2:00 pm via Zoom
- Oct 13
- Data Manipulation 3 (BOX PLOT)
- Slides
- LAB 3-AData Wrangling and Packages for Dataframes
- LAB 2 DUE
Module 3 - Data Visualization
- Oct 15
- Visual Design for Data
- Slides
- LAB 3-BCoding, mainly office hour
- OptionalData Viz Project by ferdio.
- OptionalDesign and Redesign in Data Visualization. Martin Wattenberg and Fernanda Viégas. 2015.
- Oct 20
- Exploratory Data Analysis (EDA)
- Slides
- LAB 4-ATableau
- LAB 3 DUE
- OptionalExploratory Data Analysis. United States Environmental Protection Agency.
- Oct 22
- Tableau (Online Session)
- Slides
- Instructor leave due to ACSP 2025
- LAB 4-BTableau
- Oct 27
- Perception, Color, Fonts
- Slides
- LAB 5-AVisualization using Programming Languages
- LAB 4 DUE
- Oct 29
- Visualization using Programming Languages
- Slides
- LAB 5-BCoding
- Oct 31
- Optional Adobe Suites
- Online Session at 1:00 - 2:00 pm via Zoom
- Nov 03
- Interaction and Dashboard
- Slides
- LAB 6-ACoding
- LAB 5 DUE
- Nov 05
- Interaction and Dashboard
- Slides
- LAB 6-BCoding
Module 5 - Advanced Topics and Final Projects
- Nov 24
- Storying Telling, Web Publishing, Text Analysis, etc.
- Slides
- LAB 8 DUE
- Nov 26
- Introduction to Machine Learning (Cluster, Decision Trees)
- Slides
- Dec 01
- Introduction to Artificial Intelligence and Data Ethnics
- Slides
- OptionalAI for Social Good. Nature Communications. Nenad Tomašev et al. 2020.
- OptionalA Golden Decade of Deep Learning: Computing Systems & Applications. Jeffrey Dean (UW Alumni, Google). 2022.
- OptionalStatistical Modeling: The Two Cultures. Leo Breiman. 2001.
- OptionalWhat is a Neural Network. 3Blue1Brown. 2017.
- OptionalAtlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Kate Crawford. 2022.
- OptionalA Brief Overview of AI governance for Responsible Machine Learning Systems. Navdeep Gill et al. 2022
- Dec 03
- Final Project Presentation
- Final Project Instruction
- Dec 12
- Final Project Submission
- Final Project Instruction
- Final Project DUE
- Dec 12
- Final Week
- Final Project Instruction
- Final Project DUE
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Built on Just the Class developed by Kevin Lin at Allen School