Logo
International Journal of
Research in Advanced Engineering and Technology
ARCHIVES
VOL. 2, ISSUE 4 (2016)
Big data analytics in engineering and science curriculum restructuring using singular value decomposition (SVD)
Authors
Ozor Godwin O, Nwobodo Lois O, Oleka Chioma V
Abstract

With the availability of huge data in the internet and other web supported devices. It was reported by other researchers that lesser percentage of the data were being used. Engineering and Science curriculum need extensive review and restructuring to improve employability of the graduates and also, to meet the needs of the industry. In this paper, critical areas like: communication skills; problem solving skills; entrepreneur skills; environmental awareness; lifelong learning; information management; teamwork; ethics and moral were considered for course(s) to be taught in the faculty of engineering and science. Singular value decomposition was applied to align the component of effective real-world training pattern to bridge the gap between academic and industry. Matlab was used to simulate the model.

Download
Pages:11-14
How to cite this article:
Ozor Godwin O, Nwobodo Lois O, Oleka Chioma V "Big data analytics in engineering and science curriculum restructuring using singular value decomposition (SVD)". International Journal of Research in Advanced Engineering and Technology, Vol 2, Issue 4, 2016, Pages 11-14
Download Author Certificate

Please enter the email address corresponding to this article submission to download your certificate.