Using NLP to bridge Data Science Skills Gap in Namibia. A Survey

Previous studies confirm that many graduates are struggling to get jobs in the industry as they lack the required skills. Finishing high school and going to university was supposed to be the way of opening up job opportunities, which is no longer the case. The gap between industries' required skills and Higher Education Training methods is huge, even after past studies tried to find out where the problem lies. In this study, a literature survey was used to assist with the identification of existing shortcomings in training institutions, in particular the misalignment of Higher Education Training with the Industry expectations. To help understand Natural Language Processing (NLP) and how it has been applied before to solve human challenges problems. The ultimate goal is to design a model that helps bridge the skills gap between academic institutions and the industry. This model will have a component of mining data from existing curriculum documentation of Data Science, the results are to be reviewed and compared to the industry expected skillset to help design a preferred curriculum. The study used methods of research, analysis and data collection based on the mixed method of qualitative, survey distribution for deep understanding on how they are picking up this skills gap and what they recommend should be done to bridge the gap. This study is mainly focused on the Computing faculty in the Namibia University of Science and technology and First National Bank Namibia, which are considered to have or plan to have a data science department in the years to come. The results from this research are significant as they align the academic system to the skills required in the industry.