This course provides foundational programming, data science, and software engineering knowledge using Python. Through a combination of lectures, hands-on exercises, and real-world case studies related to transportation data science, participants develop practical skills and knowledge for creating simple programs to analyze datasets, implement algorithms, conduct simulations, and more.

This course introduces microscopic traffic simulation using SUMO. It has two phases: first, students learn to build networks, generate demand, and calibrate models to match real data. Second, they design future scenarios (e.g., infrastructure or demand changes) and implement traffic control using Python and TraCI, presenting solutions to traffic bottlenecks.