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http://dx.doi.org/10.22693/NIAIP.2021.28.2.034

A Curriculum Study to Strengthen AI and Data Science Job Competency  

Kim, Hyo-Jung (Graduate School of Information, Yonsei University)
Kim, Hee-Woong (Graduate School of Information, Yonsei University)
Publication Information
Informatization Policy / v.28, no.2, 2021 , pp. 34-56 More about this Journal
Abstract
According to the Fourth Industrial Revolution, demand for and interest in jobs in the field of AI and data science - such as artificial intelligence/data analysts - are increasing. In order to keep pace with this trend, and to supply human resources that can effectively perform such jobs in the relevant fields in a timely manner, job seekers must develop the competencies required by the companies, and universities must be in charge of training. However, it is difficult to devise appropriate response strategies at the level of job seekers, companies and universities, which are stakeholders in terms of supplying suitably competent personnel. Therefore, the purpose of this study is to determine which competencies are required in practice in order to cultivate and supply human talents equipped with the necessary job competencies, and to propose plans for the development of the required competencies at the university level. In order to identify the required competencies in the field of AI and data science, data on job postings on the LinkedIn site, the recruitment platform, were analyzed using text mining techniques. Then, research was conducted with the aim of devising and proposing concrete plans for competency development at the university level by comparing and verifying the results of the international graduate school curriculum in the field of AI and data science, and the interview results with the hiring managers, respectively, with the results of the topic model.
Keywords
AI job competency; text mining; network analysis; curriculum; topic model; interview;
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