An artificial intelligence course for chemical engineers
- Author(s)
- Min Wu, Ulderico Di Caprio, Florence Vermeire, Peter Hellinckx, Leen Braeken, Steffen Waldherr, M. Enis Leblebici
- Abstract
Artificial intelligence and machine learning are revolutionising fields of science and engineering. In recent years, process engineering has widely benefited from this novel modelling and optimisation approach. The open literature can offer several examples of their applications to chemical engineering problems. Increasing investments are devoted to these techniques from different industrial areas, but insufficient information on a structured course covering these topics in a chemical engineering curriculum could be found. The course in this paper intends to reduce this gap. We introduce one of the first courses on artificial intelligence applications in a chemical engineering curriculum. The course targets Master's students with a chemical engineering background and insufficient knowledge of statistical approaches. It covers the main aspects by utilising frontal lectures and hands-on exercises with active learning methods. This paper shows the methodology we adapted to introduce students to machine learning techniques and how they responded to each class. The student performances for each test are shown, as well as the survey results based on student feedback and suggestions. This work contains essential guidelines for educators who will provide an artificial intelligence course in a chemical engineering curriculum.
- Organisation(s)
- Functional and Evolutionary Ecology
- External organisation(s)
- Katholieke Universiteit Leuven, Leuven (Arenberg), University of Antwerp
- Journal
- Education for Chemical Engineers
- Volume
- 45
- Pages
- 141-150
- No. of pages
- 10
- ISSN
- 1749-7728
- DOI
- https://doi.org/10.1016/j.ece.2023.09.004
- Publication date
- 10-2023
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 102001 Artificial intelligence
- Keywords
- ASJC Scopus subject areas
- Education, Chemical Engineering(all)
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/an-artificial-intelligence-course-for-chemical-engineers(dcbcf81a-67cc-4d51-9738-e118e422b7cb).html