SPyCE: A structured and tailored series of Python courses for (bio)chemical engineers

Abstract

In times of educational disruption, significant advances in adopting digitalization strategies have been accelerated. In this transformation climate, engineers should be adequately educated to face the challenges and acquire the new skills imposed by Industry 4.0. Among these, one of the most highly requested tools is Python. To tackle these aspects, this work establishes a pedagogical framework to teach Python to chemical engineers. This is achieved through a hands-on series of Python courses (sPyCE), covering topics as chemical reaction engineering and machine learning. Part of the series has been embedded in the curriculum of a Bachelor’s-level course at the Technical University of Denmark (DTU). Overall, students found the course to be useful; using Python, they solved systems of differential equations, mass and energy balances, set stoichiometric tables, regressions, simulations and more. Motivated by the large applicability and relevance of the covered topics, sPyCE is made publicly available on GitHub.