CEE412/ CET522 Transportation Data Management and Visualization (Win 22)

Testimonials

  • I wish I could have had such a course in my graduate program. These concepts and skills are exactly what I need now in my job. Rarely did I analyze datasets larger than 10MB in school. –– Jayne, our conslutant speaker

  • Overall, I really liked the class structure and I feel that I actually learn and want to do the assignments. And the number of assignments I think is perfect with the projects because the majority of where I really learned how to use functions and in what ways to use them was from the Projects especially Project 2. –– Arthur, MS student

  • I really enjoyed the course! –– Thong, BS student

  • Thanks for teaching a great course! –– William, BS student

Basic Info (Syllabus)

  • Lectures: WF 8:30-9:50am, ECE 037 or online (following university's policy)

  • Teaching Team

    • Instructor: Shuyi Yin (syin1@uw.edu), Th 2-4pm, MOR 101 or online

    • Grader: Fengze (Fraser) Yang (fy2022@uw.edu), T 1-2pm, MOR 101 or online

  • Course Description
    At the heart of modern transportation challenges is the need for good data. As big data is bringing new opportunities, however, the transportation industry is overwhelmed with the unprecedented volume, variety, velocity, and veracity. How to manage modern transportation data streams effectively, to process them efficiently, and to extract insights from them, have been the critical challenges faced by the professionals. This course starts from fundamental concepts and applications of database design and management, touches analysis of example transportation data sets via Python, and leverages state-of-the-art open-sourced visualization tools to communicate. Contents are organized in two modules, i.e., SQL-centric data management, and Python-based analysis and visualization. Students will gain hands-on experience with coding, critical thinking, and professional communications, both individually and in teams.

  • Course Objective

    • Become familiar with basic database design and management concepts.

    • Learn/ improve coding SQL queries to manage and analyze data, e.g., in Microsoft SQL Server.

    • Understand basic Python data structures, gain fundamental skills in data wrangling via Pandas, and practice to communicate via visualization, e.g., in Folium and Streamlit.

    • Learn to design, validate, present, and review data analysis projects on transportation data.

  • Grading

    • 40% Four Assignments + 20% Midterm + 40% Two Project Pieces

Example Student Project Outcomes

Schedule

Week Day Date Topic Location Items Projects
1 Wed Jan. 5 Introduction and Course Overview [Slides] Online
Fri Jan. 7 Introduction to Databases [Slides] Online
2 Wed Jan. 12 TRB Conference week – E/R Diagram [Slides] Recorded
Fri Jan. 14 TRB Conference week – Relational Data Model [Slides] Online A1 Out
3 Wed Jan. 19 Database Schema Design Exercise [Slides] Online
Fri Jan. 21 Structured Query Language (SQL) I [Slides] Online A1 Due
4 Wed Jan. 26 Structured Query Language (SQL) II [Slides] ECE 037 A2 Out P1 Out [PDF]
Fri Jan. 28 Structured Query Language (SQL) III [Slides] ECE 037
5 Wed Feb. 2 Structured Query Language (SQL) IV [Slides] ECE 037
Fri Feb. 4 Advanced SQL and Intro to Distributed Data Processing [Slides] ECE 037 A2 Due
6 Wed Feb. 9 Midterm 1 Hybrid
Fri Feb. 11 Introduction to Python (data structures, some useful modules) [Notebook] Online
7 Wed Feb. 16 Data Wrangling and Connecting to Databases with Pandas [Slides],[Notebook] Online A3 Out P1 Due
Fri Feb. 18 Geospatial Data Wrangling with GeoPandas [Notebook] Online P2 Out [PDF]
8 Wed Feb. 23 Case studies: traffic safety (HSIS/ NTD), traffic prediction (loop detector) [Slides] Online
Fri Feb. 25 Case studies: multi sources (LiDAR + signal timing), new mobilities (NYC TLC data) [Slides] Online A3 Due
9 Wed Mar. 2 Intro to Data Visualization [Slides] [Notebook] Online
Fri Mar. 4 Data pipeline & web application (Streamlit) [Notebook] Online A4 Out
10 Wed Mar. 9 Streamlit Exercise & Project OH Hybrid
Fri Mar. 11 Guest Lecture Online
11 Tue Mar. 15 Final Project Presentations (8:30-10:20am) ECE 037 P2 pre Due
11 Wed Mar. 16 Final Project Report and Data App A4 Due P2 report Due

Guest Speakers (8:30 - 9:50am on Mar 11)

The Pulpit Rock