Mathematical Modeling for Computational Science
APMTH 215
Subject & Catalog Number
Course Information
Description
Mathematical modeling is the essential component of the revolution in computation-based research over the past decade. While designing mathematical models is itself an art form, it is equally important to learn how to transform them into computational systems that allow robust evaluation, which is critical for real-world use cases, from modeling the spread of COVID, to designing better large language models. This course introduces mathematical modeling ideas while teaching how to transform them into robust computational frameworks for model evaluation and deployment, as done in industry. The aim is to give both a broad view of “what a mathematical model” is and, at the same time, to teach the core computational skills for building usable state-of-the-art models. Topics drawn from biology, economics, engineering, physical and social sciences.
Course Notes
This class is taught in parallel to the undergraduate class Applied Math 115. Preference will be given to Data Science and CSE SM Students and then other graduate students.
Recommended Prep
Computer programming background. Statistics 110, Applied Mathematics 105.
Available for Harvard Cross Registration
NOTE: This course requires additional sections; you will be prompted to choose secondary components during the Add to Cart process
