An Undergraduate Curriculum for Deep Learning

Guzin Tirkes, C. Ekin, Gökhan engul, Atila Bostan, M. Karakaya
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引用次数: 2

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.
深度学习本科课程
深度学习(DL)是一个有趣且快速发展的研究领域,目前已被用作工业和许多学科的一部分,以解决从图像分类,计算机视觉,视频游戏,生物信息学,手写识别到机器翻译的广泛问题。本研究的出发点是认识到深度学习技术专家的行业需求与大学提供的足够教育的缺乏之间存在巨大差距。高等教育机构是向学生提供这种专业知识的最佳环境。然而,目前大多数大学并没有为学生提供专门设计的DL课程。因此,本研究的主要目的是设计一个包含两门课程的新课程,以促进DL主题的教与学。拟议的课程将使学生能够通过应用深度学习方法解决现实问题,并获得必要的背景知识,使他们的知识适应更先进的行业特定领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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