Geoffrey R. Hutchison. “Integrating Python into an Undergraduate Mathematics for Chemists Course” Teaching Programming across the Chemistry Curriculum, Chapter 9, pp 123-134 DOI
Many upper-level undergraduate chemistry courses, particularly quantum chemistry, thermodynamics, kinetics, and statistical mechanics, benefit from mathematical concepts beyond standard calculus, including differential equations, linear algebra, probability, statistics, operators, complex numbers, multivariate integrals, and partial derivatives. Moreover, while mathematics courses often focus on abstract problems, physical sciences, and particularly physical chemistry, offer concrete applications often with complicated functions. A one-semester course in “Mathematics for Chemists” offers a tailored syllabus specifically to address common challenges in physical and analytical courses. By including basic Python programming, students can focus on core concepts, rather than worry about common calculation or mathematical mistakes. The course includes an introduction to core Python concepts, including numpy, scipy, matplotlib, and sympy. All Jupyter notebooks and course materials are available under a Creative Commons license from https://github.com/ghutchis/chem1000.