Withdraw
Loading…
Employer's perspective on data science: An analysis on job requirements- learning objectives
Behpour, Sahar; Goudarzi, Abbas; Hawamdeh, Suliman
Content Files

Loading…
Download Files
Loading…
Download Counts (All Files)
Loading…
Edit File
Loading…
Permalink
https://hdl.handle.net/2142/105342
Description
- Title
- Employer's perspective on data science: An analysis on job requirements- learning objectives
- Author(s)
- Behpour, Sahar
- Goudarzi, Abbas
- Hawamdeh, Suliman
- Issue Date
- 2019-09-24
- Keyword(s)
- Artificial intelligence
- Data curation
- Data visualization
- Discovery systems
- Machine learning
- Date of Ingest
- 2019-08-23T21:51:55Z
- 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.
- Series/Report Name or Number
- Artificial intelligence
- Data curation
- Data visualization
- Discovery systems
- Machine learning
- Type of Resource
- text
- Genre of Resource
- Conference Paper / Presentation
- Permalink
- http://hdl.handle.net/2142/105342
Owning Collections
ALISE 2019 Juried Papers PRIMARY
Manage Files
Loading…
Edit Collection Membership
Loading…
Edit Metadata
Loading…
Edit Properties
Loading…
Embargoes
Loading…