A Machine Learning Approach to Career Path Choice for Information Technology Graduates - Al-Dossari, H.; Nughaymish, F. A.; Al-Qahtani, Z.; Alkahlifah, M.; Alqahtani, A. (Engineering, Technology & Applied Science Research, 2020)
Enterprises rely more and more on well-qualified and highly specialized IT professionals. Although the increasing availability of IT jobs is a good indicator for IT graduates, they nonetheless may find themselves confused about the most appropriate career for their future. In this paper, a recommendation system called CareerRec is proposed, which uses machine learning algorithms to help IT graduates select a career path based on their skills. CareerRec was trained and tested using a dataset of 2255 employees in the IT sector in Saudi Arabia. We conducted a performance comparison between five machine learning algorithms to assess their accuracy for predicting the best-suited career path among 3 classes. Our experiments demonstrate that the XGBoost algorithm outperforms other models and gives the highest accuracy (70.47%).