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Title:Employer's perspective on data science: An analysis on job requirements- learning objectives
Author(s):Behpour, Sahar; Goudarzi, Abbas; Hawamdeh, Suliman
Subject(s):Artificial intelligence
Data curation
Data visualization
Discovery systems
Machine learning
Abstract:The strong interest in Data Science (DS) has led to the creation of a number of graduate and undergraduate programs within different academic disciplines. As academic institutions rushed to create such programs in an attempt to meet the increased demand for DS professionals, it is still not clear whether these programs are designed based on specific job requirements. In this study, we used Latent Dirichlet allocation (LDA) to conduct content analysis on job ads and program data-sets to identify terms used to represent hard and soft skills and their use in DS graduate course offerings. The findings from the study can be used to inform curriculum development of current data science programs.
Issue Date:2019-09-24
Series/Report:Artificial intelligence
Data curation
Data visualization
Discovery systems
Machine learning
Genre:Conference Paper / Presentation
Type:Text
URI:http://hdl.handle.net/2142/105342
Date Available in IDEALS:2019-08-23


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