| Autor: |
Huang, Guozhen G., Erturk, Emre, Mehdipour, Farhad |
| Zdroj: |
Journal of Applied Computing & Information Technology; 2021, Vol. 25 Issue 2, p1-10, 10p |
| Abstrakt: |
This article analyses the structure and features of the Master of Data Science courses that are offered by 21 universities in Australia and New Zealand. The primary data is a corpus of their course descriptions, outlines and other related information. The data is analysed in R for text mining of the corpus to visualise the important terms and their associations. The visualised terms are then compared with those that are drawn from 82 data scientist job descriptions that were collected in SEEK (the largest job market portal in Australia and New Zealand) over the last six months for triangulation. The primary findings are seven competency areas (subjects or units) and the proportions how the contents of these areas are distributed in the two-year course structure. It is believed that the findings will not only fill a gap in the literature of data science curriculum studies, but also provide a useful source of information for higher education institutions especially those who are interested to develop postgraduate courses in data science. The findings may also assist the professional accrediting authorities in quality assurance and evaluation of data science related courses. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
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