In this course, students will use openly accessible, global, near present-time, high-resolution satellite, 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 a developing population, 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 statistical programming language R will be used in this course.