An Undergraduate Curriculum for Deep Learning

dc.authorscopusid 36020622300
dc.authorscopusid 57203036649
dc.authorscopusid 8402817900
dc.authorscopusid 56040049800
dc.authorscopusid 16637174900
dc.contributor.author Tirkes,G.
dc.contributor.author Ekin,C.C.
dc.contributor.author Engul,G.
dc.contributor.author Bostan,A.
dc.contributor.author Karakaya,M.
dc.contributor.other Computer Engineering
dc.date.accessioned 2024-07-05T15:45:13Z
dc.date.available 2024-07-05T15:45:13Z
dc.date.issued 2018
dc.department Atılım University en_US
dc.department-temp Tirkes G., Department of Computer Engineering, Atilim University, Ankara, Turkey; Ekin C.C., Department of Computer Engineering, Atilim University, Ankara, Turkey; Engul G., Department of Computer Engineering, Atilim University, Ankara, Turkey; Bostan A., Department of Computer Engineering, Atilim University, Ankara, Turkey; Karakaya M., Department of Computer Engineering, Atilim University, Ankara, Turkey en_US
dc.description.abstract Deep Learning (DL) is an interesting and rapidly developing field of research which has been currently utilized as a part of industry and in many disciplines to address a wide range of problems, from image classification, computer vision, video games, bioinformatics, and handwriting recognition to machine translation. The starting point of this study is the recognition of a big gap between the sector need of specialists in DL technology and the lack of sufficient education provided by the universities. Higher education institutions are the best environment to provide this expertise to the students. However, currently most universities do not provide specifically designed DL courses to their students. Thus, the main objective of this study is to design a novel curriculum including two courses to facilitate teaching and learning of DL topic. The proposed curriculum will enable students to solve real-world problems by applying DL approaches and gain necessary background to adapt their knowledge to more advanced, industry-specific fields. © 2018 IEEE. en_US
dc.identifier.citationcount 2
dc.identifier.doi 10.1109/UBMK.2018.8566575
dc.identifier.endpage 609 en_US
dc.identifier.isbn 978-153867893-0
dc.identifier.scopus 2-s2.0-85060641320
dc.identifier.startpage 604 en_US
dc.identifier.uri https://doi.org/10.1109/UBMK.2018.8566575
dc.institutionauthor Bostan, Atila
dc.institutionauthor Ekin, Cansu Çiğdem
dc.institutionauthor Karakaya, Kasım Murat
dc.language.iso en en_US
dc.publisher Institute of Electrical and Electronics Engineers Inc. en_US
dc.relation.ispartof UBMK 2018 - 3rd International Conference on Computer Science and Engineering -- 3rd International Conference on Computer Science and Engineering, UBMK 2018 -- 20 September 2018 through 23 September 2018 -- Sarajevo -- 143560 en_US
dc.relation.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/closedAccess en_US
dc.scopus.citedbyCount 2
dc.subject curriculum design en_US
dc.subject Deep Learning en_US
dc.subject Deep Neural Networks en_US
dc.subject Engineering Education en_US
dc.subject Machine Learning en_US
dc.title An Undergraduate Curriculum for Deep Learning en_US
dc.type Conference Object en_US
dspace.entity.type Publication
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