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    Adana Alparslan Türkeş Science and Technology University

    Veri Bilimi ve Analitiği

    Adana, Türkiye4 yearsTaught in EnglishOpen to international students

    Why students choose this program

    • Taught in English
    • No application fee

    About Veri Bilimi ve Analitiği

    Data Science and Analytics is offered as a 4 year bachelor program at Adana Alparslan Türkeş Science and Technology University in Adana, Turkey, taught in English. The discipline focuses on extracting insights from data using statistical methods, programming, and machine learning techniques, covering the full pipeline from data collection and cleaning through analysis and visualization. Typical coursework includes programming fundamentals, statistics and probability, database systems, data mining, machine learning, and data visualization, supported by mathematics courses such as linear algebra and calculus that underpin many analytical methods. Students often work with real or simulated datasets in lab sessions and projects, gaining practical experience with the tools and workflows used in professional data analysis. Across the four years, the curriculum generally moves from foundational programming and statistics courses toward more specialized subjects such as big data systems, predictive modeling, or business analytics, depending on elective choices. Being situated at a science and technology university in Adana places data science students among peers in related computing and engineering fields, supporting collaborative and interdisciplinary project work. Graduates of data science and analytics programs commonly pursue careers as data analysts, data scientists, business intelligence specialists, and machine learning engineers, working across sectors including finance, technology, healthcare, and retail. Some graduates focus on specialized applications such as predictive analytics or data engineering, while others pursue graduate study in data science, statistics, or computer science. English-medium instruction supports engagement with the largely English-language tools, documentation, and research literature that dominate the global data science field.

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