Mapping Crash Data and Predicting Traffic Volume in New York City

This project combines data science and urban planning, equipping students to turn raw data into actionable insights using Python tools and a structured pipeline approach. Through real-world case studies, students gain hands-on experience in data gathering, analysis, and visualization, culminating in interactive narratives. Key modules include exploratory data science, geospatial analysis, and advanced machine learning, providing a solid foundation for innovative urban research.