Akademik Veri Yönetim Sistemi
1st International Data Science & Engineering Symposium (IDSES’19), Karabük, Türkiye, 30 Nisan - 03 Mayıs 2019, ss.5-7, (Özet Bildiri)
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. Data science education has to be more project-based since up to now, there is no core knowledge of data science like other sciences. It is probably the hypercorrect choice to learn this job in a university which is intertwined with industry and provides plenty of opportunity for internships. In this article, we will summarize the data science education developments and give curriculum examples from the world at the undergraduate and graduate level. Regarding these examples, every university thinks data science as he wants and the names and the contents of these programs really differs.
Keywords: Data Science, Data Product, Recommendation System.