An Undergraduate Curriculum for Deep Learning


Tirkes G., Ekin C. C., Engul G., Bostan A., Karakaya K. M.

3rd International Conference on Computer Science and Engineering, UBMK 2018, Sarajevo, Bosnia And Herzegovina, 20 - 23 September 2018, pp.604-609 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/ubmk.2018.8566575
  • City: Sarajevo
  • Country: Bosnia And Herzegovina
  • Page Numbers: pp.604-609
  • Keywords: curriculum design, Deep Learning, Deep Neural Networks, Engineering Education, Machine Learning
  • TED University Affiliated: Yes

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.