Unravelling the skills of data scientists: A text mining analysis of Dutch university master programs in data science and artificial intelligence

Mathijs J Mol, Barbara Belfi and Zsuzsa Bakk

PLOS ONE, 2024, vol. 19, issue 2, 1-14

Abstract: The growing demand for data scientists in both the global and Dutch labour markets has led to an increase in data science and artificial intelligence (AI) master programs offered by universities. However, there is still a lack of clarity regarding the specific skills of data scientists. This study addresses this issue by employing Correlated Topic Modeling (CTM) to analyse the content of 41 master programs offered by 11 Dutch universities and an interuniversity combined program. We assess the differences and similarities in the core skills taught by these programs, determine the subject-specific and general nature of the skills, and provide a comparison between the different types of universities offering these programs. Our analysis reveals that data processing, statistics, research, and ethics are the core competencies in Dutch data science and AI master programs. General universities tend to focus on research skills, while technical universities lean more towards IT and electronics skills. Broad-focussed data science and AI programs generally concentrate on data processing, information technology, electronics, and research, while subject-specific programs give priority to statistics and ethics. This research enhances the understanding of the diverse skills of Dutch data science graduates, providing valuable insights for employers, academic institutions, and prospective students.

Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0299327

DOI: 10.1371/journal.pone.0299327

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