Unraveling the Skillsets of Data Scientists: Text Mining Analysis of Dutch University Master Programs in Data Science and Artificial Intelligence
Mathijs J. Mol, Barbara Belfi, Zsuzsa Bakk

TL;DR
This study uses text mining to analyze 41 Dutch master programs in data science and AI, revealing key skills taught and differences between university types, aiding stakeholders in understanding data scientist training.
Contribution
It applies Correlated Topic Modeling to identify and compare core skills across Dutch data science and AI master programs, highlighting differences between university types.
Findings
Research, data processing, statistics, and ethics are predominant skills.
Research universities emphasize research skills; technical universities focus on IT and electronics.
Skills vary significantly between university types.
Abstract
The growing demand for data scientists in the global labor market and the Netherlands has led to a rise in data science and artificial intelligence (AI) master programs offered by universities. However, there is still a lack of clarity regarding the specific skillsets of data scientists. This study aims to address this issue by employing Correlated Topic Modeling (CTM) to analyse the content of 41 master programs offered by seven Dutch universities. 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 findings reveal that research, data processing, statistics and ethics are the predominant skills taught in Dutch data science and AI master programs, with general universities emphasizing…
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Taxonomy
TopicsComputational and Text Analysis Methods · Big Data and Business Intelligence
