DATA 444 - Agent-Based Modeling: Simulating Human Development Processes from Neighborhood to Regional Scales

Credits: (4)
Prerequisite(s): DATA 301 (formerly DATA 310) and MATH 112/MATH 132
College Curriculum: COLL 400
In this course, students will use openly accessible, global, near present-time, high-resolution satellite, household survey and CDR data, with machine learning and spatial statistics methodologies to construct agent-based models of human development processes. Each student will select and describe an administrative subdivision, its demographics, and its built and natural environments in order to estimate social and economic, complex and adapting, agent-based decision, movement and land use models. Students will construct modules that project demand for infrastructure (transportation, water, and electricity) and social services (health care, education, and public safety) as well as simulate an infectious disease outbreak, a natural disaster and unabated urbanization. The programming languages python, java, and R will be used in this course.