An Undergraduate Curriculum for Deep Learning

dc.authorscopusid36020622300
dc.authorscopusid57203036649
dc.authorscopusid8402817900
dc.authorscopusid56040049800
dc.authorscopusid16637174900
dc.contributor.authorTirkes,G.
dc.contributor.authorEkin,C.C.
dc.contributor.authorEngul,G.
dc.contributor.authorBostan,A.
dc.contributor.authorKarakaya,M.
dc.contributor.otherComputer Engineering
dc.date.accessioned2024-09-10T21:35:20Z
dc.date.available2024-09-10T21:35:20Z
dc.date.issued2018
dc.departmentAtılım Universityen_US
dc.department-tempTirkes 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, Turkeyen_US
dc.description.abstractDeep 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.citation2
dc.identifier.doi10.1109/UBMK.2018.8566575
dc.identifier.endpage609en_US
dc.identifier.isbn978-153867893-0
dc.identifier.scopusqualityN/A
dc.identifier.startpage604en_US
dc.identifier.urihttps://doi.org/10.1109/UBMK.2018.8566575
dc.identifier.urihttps://hdl.handle.net/20.500.14411/7355
dc.identifier.wosqualityN/A
dc.institutionauthorBostan, Atila
dc.institutionauthorEkin, Cansu Çiğdem
dc.institutionauthorKarakaya, Kasım Murat
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofUBMK 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 -- 143560en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectcurriculum designen_US
dc.subjectDeep Learningen_US
dc.subjectDeep Neural Networksen_US
dc.subjectEngineering Educationen_US
dc.subjectMachine Learningen_US
dc.titleAn Undergraduate Curriculum for Deep Learningen_US
dc.typeConference Objecten_US
dspace.entity.typePublication
relation.isAuthorOfPublicationd46977b1-8c5f-48c5-b14f-617a2691d9dd
relation.isAuthorOfPublication6ba797de-1a42-4c28-bbdc-867221fad30c
relation.isAuthorOfPublication93f27ee1-19eb-42dc-b4eb-a3cc7dc4b057
relation.isAuthorOfPublication.latestForDiscoveryd46977b1-8c5f-48c5-b14f-617a2691d9dd
relation.isOrgUnitOfPublicatione0809e2c-77a7-4f04-9cb0-4bccec9395fa
relation.isOrgUnitOfPublication.latestForDiscoverye0809e2c-77a7-4f04-9cb0-4bccec9395fa

Files

Collections