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Master in Data Science

From Wikipedia, the free encyclopedia

A Master of Science in Data Science is an interdisciplinary degree program designed to provide studies in scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured,[1][2] similar to data mining.

Overview

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As an area of expertise and field, data science is defined as a "concept to unify statistics, data analysis and their related quantitative and qualitative methods" in order to "understand and analyze actual phenomena" with data.[3] It employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science, in particular from the subdomains of machine learning, statistical classification, cluster analysis, data mining, databases, and visualization.

The degree is relatively new, with graduate schools, business schools, and data science centers often housing the programs. Data science degree programs have emerged to address the growing and unique need for data scientists who can provide insight into multiple organizational issues and interests across several disciplines.

When Harvard Business Review called data scientist "The Sexiest Job of the 21st Century" the term became a buzzword,[4] and is now often applied to business analytics, or even arbitrary use of data, or used as a term for statistics. While many university programs now offer a data science degree, there exists no consensus on a definition or curriculum contents.

Master in Data Science programs

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Australia

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United States

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Canada

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United Kingdom

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Ireland

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India

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Germany

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France

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Finland

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Denmark

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New Zealand

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Hong Kong

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References

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  1. ^ Dhar, Vasant (December 2013). "Data Science and Prediction". Commun. ACM. 56 (12): 64–73. doi:10.1145/2500499. ISSN 0001-0782. S2CID 6107147.
  2. ^ "The key word in "Data Science" is not Data, it is Science : Simply Statistics". simplystatistics.org. Archived from the original on 2018-08-21. Retrieved 2017-06-28.
  3. ^ Hayashi, Chikio (1998). "What is Data Science ? Fundamental Concepts and a Heuristic Example". Data Science, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Tokyo. pp. 40–51. doi:10.1007/978-4-431-65950-1_3. ISBN 978-4-431-70208-5.
  4. ^ Press, Gil. "Data Science: What's The Half-Life Of A Buzzword?". Forbes. Retrieved 2017-06-28.
  5. ^ "Earn Your Master of Science in Data Science Online".
  6. ^ "Master of Science in Data Science". CityU of Seattle. Retrieved 2023-02-23.