Abstract
Abstract: This paper investigates the gap between software engineering education and the industry needs by suggesting solutions to close that gap. The implication is that classrooms agendas are to be more flexible in nature to meet the dynamism in technology needs by the tech sector, focusing on the inclusion of current data science technologies in education programs. This study is backed by data-driven inferences which help to identify the linkage between academia and industry, and with the use of the predictive model of the regression one can estimate the graduation success. The results have proved the importance of practical skills such as research abilities, critical thinking, and problem-solving skills over traditional metrics like GPA. Thus it should be the need of the hour to develop the industry-relevant training in order to provide vocational education to students. The coordination between academia and industry fields by merging student-centric projects that have modern technologies would aid improving adapting software engineering education to the variable industrial sector. The research results emphasize the significance of an active learning process and practical application of the learned concepts that should be employed to get students ready for the challenges awaiting them at the workplace. Finally, a paper that proposes permanent developing of the engineering curriculum and close collaboration between industry and academic institutions, so that the students receive key competences to be prosperous in software engineering. Python has been implemented to analyse the skills of the software engineering curriculum for achieving the requirements of the industry. Data visualisation, data pre-processing, and predictive models have been implemented to gather data based on industrial requirements.
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