AI & Machine Learning for Urban Analytics

(3 Credit Hours) · Undergraduate

Urban regions will experience most future population growth, bringing opportunities and challenges. At the same time, advances in technology are transforming what is possible in data-driven decision-making and long-term planning in complex urban systems. This course introduces modern urban analytics through an AI/ML lens, emphasizing statistical reasoning, interpretability, and real-world urban case studies. We begin with data science essentials starting from data acquisition, exploratory data analysis (EDA), and visualization along with tools for reproducible reports. We then develop core modeling skills, progressing from classical statistical and machine learning methods to fundamental concepts in deep learning and generative AI. We will cover contemporary approaches for large-scale and complex urban data, including spatial, network, and unstructured data commonly encountered in urban studies. By the end of the semester, students will master popular methodologies, and gain hands-on skills in turning urban data into actionable insights.