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How Should Data Science Education Be?
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Author(s): Necmi Gürsakal (Fenerbahçe University, Ataşehir, Turkey), Ecem Ozkan (Uludag University, Bursa, Turkey), Fırat Melih Yılmaz (Uludağ University, Bursa, Turkey)and Deniz Oktay (Uludağ University, Bursa, Turkey)
Copyright: 2020
Volume: 9
Issue: 2
Pages: 12
Source title:
International Journal of Energy Optimization and Engineering (IJEOE)
Editor(s)-in-Chief: Jose Marmolejo-Saucedo (National Autonomous University of Mexico), Gerhard-Wilhelm Weber (Poznań University of Technology, Poland)and Pandian Vasant (Ton Duc Thang University, Vietnam)
DOI: 10.4018/IJEOE.2020040103
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Abstract
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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