Urban Analytics

(3 Credit Hours) · Undergraduate

Urban regions will experience most future population growth, bringing opportunities and challenges. At the same time, statistical/machine learning has been evolving rapidly in the era of big data and provides tools to inform both data-driven decision-making and long-term planning in complex urban systems. Focusing on methodologies with statistical reasoning, the course brings in a large set of cutting-edge machine learning techniques combined with up-to-date urban case studies. We will start with data science essentials starting from data acquisition, exploratory data analysis (EDA), and visualization along with tools for reproducible reports. We next show how to build and interpret basic models; then we go beyond and focus on contemporary methods and techniques for handling large and complex urban data. By the end of the semester, students will master popular modern statistical methods, but also get equipped with hands-on skills in urban data analytics.