Harvard T.H. Chan School of Public Health
Semester: Spring 2
This new advanced-level course offered by CHDS faculty Zachary Ward focuses on statistical and computational methods that are applicable for disease modelling in public health and medicine. Students will learn to apply state-of-the-art methods related to three core modules: 1) Numerical Methods, 2) Simulation-based Inference, and 3) High Performance Computing. This course is primarily intended for quantitative doctoral students (e.g., decision science, epidemiology, biostatistics), but is also open to advanced master’s students with an interest in computational science.
Prerequisites include a course in mathematical modeling (RDS 285 or RDS 288), probability and statistics (BST201 or ID201 or (BST 206 and BST 207)), and basic knowledge of mathematical notation and reasoning. Prior programming experience (e.g., R, Python, C++, Java) is strongly recommended.
