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ThinkMind // eLmL 2020, The Twelfth International Conference on Mobile, Hybrid, and On-line Learning // View article elml_2020_3_30_50024


Addressing Prerequisites for STEM Classes Using an Example of Linear Algebra for a Course in Machine Learning

Authors:
Genady Grabarnik
Luiza Kim-Tyan
Serge Yaskolko

Keywords: prerequisites; machine learning; linear algebra; interactive self-study course; jupyter notebooks

Abstract:
Abstract—While teaching Science, Technology, Engineering, and Mathematics (STEM) subjects, we frequently encounter situations where we have several prerequisites for a particular course. We anticipate that students will have different levels of knowledge in these prerequisites. A prerequisite (Linear algebra for Machine Learning course) was implemented as an interactive online course using Jupyter Notebooks and nbgrader. A preliminary survey shows a preference by students and instructors for this interactive implementation.

Pages: 57 to 62

Copyright: Copyright (c) IARIA, 2020

Publication date: March 22, 2020

Published in: conference

ISSN: 2308-4367

ISBN: 978-1-61208-764-1

Location: Valencia, Spain

Dates: from November 21, 2020 to November 25, 2020

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