Kształcenie specjalistów z zakresu data science na poziomie studiów wyższych w Europie

Autor

  • Katarzyna Jarczewska-Walendziak Uniwersytet Mikołaja Kopernika w Toruniu
  • Małgorzata Kowalska-Chrzanowska Uniwersytet Mikołaja Kopernika w Toruniu
  • Przemysław Krysiński Uniwersytet Mikołaja Kopernika w Toruniu

DOI:

https://doi.org/10.24917/20811861.19.37

Słowa kluczowe:

data science, data scientist, higher education, curricula, Europe

Abstrakt

Purpose: The aim of the paper is to analyse educational programs of data science at institutions of higher learning in Europe for the 2020-2021 academic year. The authors try to answer the following questions: What are the education possibilities for individuals, who would like to follow the professional path of data science analytics? Where and how one may obtain the required competences? What competences may be earned during higher studies? What professions are predestined by data science studies? Design/methodology/approach: The authors conduct the analysis of 100 randomly selected bachelor, major and post-graduate curricula that are found in the didactic offer of various institutions of higher learning. The basic information about the offered courses have been obtained through individual searches in the resources of a number of Internet portals (e.g. Studies in Europe, Academiccourses.com, Studia.gov.pl, Postgrad.com and MastersPortal.com). On the basis of information provided in websites of every indicated institution of higher learning, the characterisation of studies was conducted, with consideration for the following criteria: branch name, academic unit, description of curriculum (preliminary requirements, offered knowledge and skills, potential employment), duration of learning, course type, subject taught. Findings: The conducted research prove the diversity with respect to the offered forms of data scientists’ education. In Europe, this curriculum is offered at bachelor level by ca. 30 institutions of higher learning, at major level - by ca. 170 institutions and at post-graduate level - by ca. 350 institutions. The most varied educational contents are offered in post-graduate courses. All study programs identified by the authors are profiled for the needs of certain disciplines - especially IT and mathematics, statistics and economy. The candidates for higher learning courses are often expected to possess advanced skills in the scope of ICT, and often also professional experience in the field of data analysis. The majority of courses is paid. Depending on the level of education, the course lasts from one to four years. Study programs are dominated by IT subjects, enriched with general curriculum subject modules. The majority of branches makes it possible to earn knowledge and skills in the field of IT and exact sciences, especially the methods of aggregating, storing and processing of Big Data, the rules of correct and effective programming, performing statistical analyses and interpreting their results. Among the identified branches of studies, the surprising is the small number of opportunities directly addressed to graduates of the humanities’ studies, including the widely understood information studies (information management, information broking, library science, information architecture, information science).

Bibliografia

Standard Occupational Classification System, 2018, [on-line:] https://www.bls.gov/soc/2010/2010_major_groups.htm – 30.03.2021.

Academiccourses.com, 2020, [on-line:] https://www.academiccourses.com/ – 30.03.2021.

Adhikari A., DeNero J., Wagner D., Computational and Inferential Thinking: The Foundations of Data Science, 2021, [on-line:] https://www.inferentialthinking.com/ – 30.03.2021.

Birkbeck, University of London: Applied Data Science, 2020, [on-line:] http://www.bbk.ac.uk/study/2020/postgraduate/ programmes/TPCCOMIP_C – 30.03.2021.

Birmingham City University: Big Data Analytics, 2020, [on-line:] https://www.bcu.ac.uk/courses/big-data-analytics-msc-2020-21 – 30.03.2021.

Bournemouth University: Data Science & Analytics: Course Details, 2020, [on-line:] https://www.bournemouth.ac.uk/study/courses/bsc-hons-data-science-analytics – 30.03.2021.

Bournemouth University: Data Science and Analytics: Programme Specification – Purpose and Guidance for Completion, 2020, [on-line:] https://intranetsp.bournemouth.ac.uk/progspecs/bsc-data-science-and-analytics.pdf – 30.03.2021.

Brynko B., Data Scientists: You Sexy Thing (Cover Story), „Information Today” 2013, vol. 30, no. 10, s. 1–36.

Compare All Types of Data Science Degrees, 2021, [on-line:] https://www.datascienceprograms.org/ – 30.03.2021.

Czech University of Life Sciences: Environmental Data Science, 2020, [on-line:] https://www.fzp.czu.cz/en/r-9408-study/r-9495-study-programmes/r-9744-bachelor-s-study-programmes/r-14239-environmental-data-science – 30.03.2021.

Czech University of Life Sciences: Study plan BEDS, 2020, [on-line:] https://www.fzp.czu.cz/dl/71175?lang=en – 30.03.2021.

Danyluk A., Leidig P. i in., Computing Competencies for Undergraduate Data Science Programs: An ACM Task Force Final Report, [w:] SIGCSE 2021 – Proceedings of the 52nd ACM Technical Symposium on Computer Science Education, New York 2021, s. 1119–1120.

Data Science for Undergraduates: Opportunities and Options, 2018, [on-line:] https://www.nap.edu/catalog/25104/data-science-for-undergraduates-opportunities-and-options – 30.03.201.

Davenport T. H, DJ Patil, Data Scientist: The Sexiest Job of the 21st Century, „Harvard Business Review” 2012, October, [on-line:] https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century – 30.03.2021.

Demchenko Y., The Emerging Role of the Data Scientist and the Experience of Data Science Education at the University of Amsterdam, [w:] LEARN Toolkit of Best Practice for Research Data Management, London 2017, s. 105–115.

Foote K. D., A Brief History of Data Science, 2016, [on-line:] https://www.dataversity.net/brief-history-data-science/ – 30.03.2021.

Hicks S. C., Irizarry R. A., A Guide to Teaching Data Science, „The American Statistician” 2018, vol. 72, no. 4, s. 382–391.

Irizarry R. A., The Role of Academia in Data Science Education, „Harvard Data Science Review” 2020, vol. 2, no. 1.

Klassifikation der Berufe 2010: Systematik und Verzeichnisse der KldB 2010, 2013, [on-line:] https://statistik.arbeitsagentur.de/DE/Navigation/Grundlagen/Klassifikationen/Klassifikation-der-Berufe/KldB2010/Systematik-Verzeichnisse/Systematik-Verzeichnisse-Nav.html – 30.03.2021.

KU Leuven: Postgraduate Studies: Big Data & Analytics in Business and Management, 2020, [on-line:] https://feb.kuleuven.be/permanente-vorming/bigdataanalytics – 30.03.2021.

KU Leuven: Postgraduate Studies: Big Data & Analytics in Business and Management: Brochure, 2020, [on-line:] https://feb.kuleuven.be/permanente-vorming/postgraduatebigdatabrochure/ – 30.03.2021.

MastersPortal.com, 2020, [on-line:] https://www.mastersportal.com/ – 30.03.2021.

Meng X.-L., Data Science: An Artificial Ecosystem, „Harvard Data Science Review” 2019, vol. 1, no. 1.

Naur P., The Science of Datalogy, „Communications of the ACM” 1966, vol. 9, no. 7, s. 485.

Politechnika Warszawska: Data Science, 2020, [on-line:] http://datascience.ii.pw.edu.pl/datascience.html – 30.03.2021.

Postgrad.com, 2020, [on-line:] https://www.postgrad.com/ – 30.03.2021.

Studies in Europe, 2020, [on-line:] https://www.studies-in-europe.eu/ – 30.03.2021.

Tang R., Sae-Lim W., Data Science Programs in U.S. Higher Education: An Exploratory Content Analysis of Program Description, Curriculum Structure, and Course Focus, „Education for Information” 2016, vol. 32, no. 3, s. 269–290.

The Age of Analytics: Competing in a Data-Driven World, 2016, [on-line:] https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-age-of-analytics-competing-in-a-data-driven-world – 30.03.2021.

Tomoyuki H., Data Scientist: A Key Factor in Innovation Driven by Big Data, „Journal of Information Processing & Management” 2013, vol. 56, no. 1, s. 2–11.

Universidad Pontificia Comillas: Master in Big Data Technologies and Advanced Analytics, 2020, [on-line:] https://www.comillas.edu/postgrado/master-en-big-data-tecnologia-y-analitica-avanzada – 30.03.2021.

University of Campania „Luigi Vanvitelli”: Bachelor’s Degree in Data Analytics, 2020, [on-line:] https://www.matfis.unicampania.it/didattica/corsi-di-studio/data-analytics/2-non-categorizzato/117-bachelor-s-degree-in-data-analytics – 30.03.2021.

University of Campania „Luigi Vanvitelli”: Bachelor’s Degree in Data Analytics: Study Plan, 2020, [on-line:] https://www.matfis.unicampania.it/images/didattica/ triennale_analytics/piano_studi/piano_studi_Data_Analytics_2019_2020.pdf – 30.03.2021.

Uniwersytet Warszawski: Data Science and Business Analytics, [on-line:] https://www.wne.uw.edu.pl/en/candidates/data-science/ – 12.05.2020.

Woodie A., Why Data Science Is Still a Top Job, 2020, [on-line:] https://www.datanami.com/2020/11/16/why-data-science-is-still-a-top-job/ – 30.03.2021.

Pobrania

Opublikowane

2021-12-20

Jak cytować

Jarczewska-Walendziak, K., Kowalska-Chrzanowska, M., & Krysiński, P. (2021). Kształcenie specjalistów z zakresu data science na poziomie studiów wyższych w Europie. AUPC Studia Ad Bibliothecarum Scientiam Pertinentia, 19, 602–620. https://doi.org/10.24917/20811861.19.37

Numer

Dział

Artykuły / Articles