Computing for Mathematics.

Catalog description

This course introduces graduate students to essential computational tools and methodologies—including LaTeX typesetting, programming in Python and R, numerical analysis, data visualization, simulation techniques, and algorithmic thinking—that serve as the foundation for advanced studies in applied mathematics, mathematical modeling, probability, statistics, image processing, and cryptography. SU, 8-wk, Asynchronous.