Introducing and Integrating Machine Learning in an Operations Research Curriculum: An Application-Driven Course

Autor/inn/en	Boutilier, Justin J.; Chan, Timothy C. Y.
Titel	Introducing and Integrating Machine Learning in an Operations Research Curriculum: An Application-Driven Course
Quelle	In: INFORMS Transactions on Education, 23 (2023) 2, S.64-83 (20 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Boutilier, Justin J.) ORCID (Chan, Timothy C. Y.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
Schlagwörter	Artificial Intelligence; Operations Research; Undergraduate Students; Engineering Education; Active Learning; Data Analysis; Course Objectives; Foreign Countries; Student Evaluation; Canada; Wisconsin (Madison) + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Ingenieurausbildung; Aktives Lernen; Auswertung; Ausland; Schulnote; Studentische Bewertung; Kanada
Abstract	Artificial intelligence (AI) and operations research (OR) have long been intertwined because of their synergistic relationship. Given the increasing popularity of AI and machine learning in particular, we face growing demand for educational offerings in this area from our students. This paper describes two courses that introduce machine learning concepts to undergraduate, predominantly industrial engineering and operations research students. Instead of taking a methods-first approach, these courses use real-world applications to motivate, introduce, and explore these machine learning techniques and highlight meaningful overlap with operations research. Significant hands-on coding experience is used to build student proficiency with the techniques. Student feedback indicates that these courses have greatly increased student interest in machine learning and appreciation of the real-world impact that analytics can have and helped students develop practical skills that they can apply. We believe that similar application-driven courses that connect machine learning and operations research would be valuable additions to undergraduate OR curricula broadly. (As Provided).
Anmerkungen	Institute for Operations Research and the Management Sciences (INFORMS). 5521 Research Park Drive Suite 200, Catonsville, Maryland 21228. Tel: 800-446-3676; Tel: 443-757-3500; Fax: 443-757-3515; e-mail: informs@informs.org; Web site: https://pubsonline.informs.org/journal/ited
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01