揭示数据科学家的技能:荷兰大学数据科学和人工智能硕士课程的文本挖掘分析

Mathijs J. Mol, Barbara Belfi, Zsuzsa Bakk
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引用次数: 0

摘要

全球劳动力市场和荷兰对数据科学家的需求不断增长,导致大学提供的数据科学和人工智能(AI)硕士课程有所增加。然而,对于数据科学家的具体技能仍然缺乏明确的认识。本研究旨在通过使用相关主题模型(CTM)分析荷兰7所大学提供的41个硕士课程的内容来解决这一问题。我们评估了这些课程所教授的核心技能的异同,确定了这些技能的特定学科和一般性质,并在提供这些课程的不同类型的大学之间进行了比较。我们的研究结果显示,研究、数据处理、统计和道德是荷兰数据科学和人工智能硕士课程教授的主要技能,普通大学强调研究技能,技术大学更侧重于IT和电子技能。这项研究有助于更好地理解数据科学家的各种技能,这对雇主、大学和未来的学生来说是至关重要的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unraveling the Skillsets of Data Scientists: Text Mining Analysis of Dutch University Master Programs in Data Science and Artificial Intelligence
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 research skills and technical universities focusing more on IT and electronic skills. This study contributes to a better understanding of the diverse skillsets of data scientists, which is essential for employers, universities, and prospective students.
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