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Self-Contained Jupyter Notebook Labs Promote Scalable Signal Processing Education

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Self-Contained Jupyter Notebook Labs Promote Scalable Signal Processing Education

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Carrano, D.; Chugunov, I.; Lee, J.; Ayazifar, B. (2020). Self-Contained Jupyter Notebook Labs Promote Scalable Signal Processing Education. Editorial Universitat Politècnica de València. 1409-1416. https://doi.org/10.4995/HEAd20.2020.11308

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/146081

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Title: Self-Contained Jupyter Notebook Labs Promote Scalable Signal Processing Education
Author: Carrano, Dominic Chugunov, Ilya Lee, Jonathan Ayazifar, Babak
Issued date:
Abstract:
[EN] Our upper-division course in Signals and Systems at UC Berkeley comprises primarily sophomore and junior undergraduates, and assumes only a basic background in Electrical Engineering and Computer Science. We’ve ...[+]
Subjects: Higher Education , Learning , Educational systems , Teaching , Python , Jupyter Notebooks , Virtual labs , Educational technology , Signals and systems , Electrical engineering.
Copyrigths: Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
ISBN: 9788490488119
Source:
6th International Conference on Higher Education Advances (HEAd'20).
DOI: 10.4995/HEAd20.2020.11308
Publisher:
Editorial Universitat Politècnica de València
Publisher version: http://ocs.editorial.upv.es/index.php/HEAD/HEAd20/paper/view/11308
Conference name: Sixth International Conference on Higher Education Advances
Conference place: València, Spain
Conference date: Junio 02-05,2020
Type: Capítulo de libro Comunicación en congreso

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