Bostan, Atila

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https://hdl.handle.net/20.500.14411/7717
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B., Atila
A., Bostan
Bostan,A.
Bostan, Atila
A.,Bostan
B.,Atila
Atila, Bostan
Job Title
Doktor Öğretim Üyesi
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atila.bostan@atilim.edu.tr
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Computer Engineering
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Former Staff
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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 -- 1435604
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2nd International Conference on Computer Science and Engineering, UBMK 2017 -- 2nd International Conference on Computer Science and Engineering, UBMK 2017 -- 5 October 2017 through 8 October 2017 -- Antalya -- 1321161
9th International Conference on Electronics Computer and Computation (ICECCO 2012) -- NOV 01-03, 2012 -- Ankara, TURKEY1
CEUR Workshop Proceedings -- 7th Turkish National Software Engineering Symposium, UYMS 2013 -- 26 September 2013 -- Izmir -- 1111441
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Author: Karakaya, MuratSubject: curriculum design

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    An Undergraduate Curriculum for Deep Learning
    (Ieee, 2018) Tirkes, Guzin; Ekin, Cansu Cigdem; Sengul, Gokhan; Bostan, Atila; Karakaya, Murat
    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.