数据科学教育应该是怎样的?

Pub Date : 2020-04-01 DOI:10.4018/ijeoe.2020040103
N. Gürsakal, Ecem Ozkan, F. Yilmaz, Deniz Oktay
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引用次数: 0

摘要

近年来,人们对数据科学的兴趣越来越大。数据科学,包括数学、统计学、大数据、机器学习和深度学习,可以被认为是统计学、数学和计算机科学的交叉点。尽管关于数据科学核心领域的争论仍在继续,但这个主题已经大受欢迎。大学对数据科学有很高的需求。他们正试图通过开设研究生和博士课程来满足这一需求。由于该学科是一个新领域,因此各大学提供的数据科学课程之间存在显着差异。此外,由于该学科与统计学比较接近,很多时候,数据科学专业都是在统计系开设的,这也造成了专业之间的差异。在本文中,我们将总结数据科学教育在世界上的发展,特别是在土耳其,以及数据科学教育应该如何在研究生阶段进行。
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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How Should Data Science Education Be?
The interest in data science is increasing in recent years. Data science, including mathematics, statistics, big data, machine learning, and deep learning, can be considered as the intersection of statistics, mathematics and computer science. Although the debate continues about the core area of data science, the subject is a huge hit. Universities have a high demand for data science. They are trying to live up to this demand by opening postgraduate and doctoral programs. Since the subject is a new field, there are significant differences between the programs given by universities in data science. Besides, since the subject is close to statistics, most of the time, data science programs are opened in the statistics departments, and this also causes differences between the programs. In this article, we will summarize the data science education developments in the world and in Turkey specifically and how data science education should be at the graduate level.
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