Predictive Analytics of Industry Skills Gaps: Using Machine Learning – In Case of Tilahun Yigzaw TVET College

Abstract

Although Technical and Vocational Education and Training (TVET) have gained increasing significance, many graduates remain unable to secure employment due to a persistent mismatch between the skills they acquire and the requirements of the labor market. This issue continues to contribute to high levels of unemployment among trainees. Within this context, this study attempts to analyze Tilahun Yigzaw TVET College in Tigray, Ethiopia. The research concludes that predictive analytics have the potential to enhance data-driven decision-making in TVET institutions by identifying critical factors influencing the skills gap and facilitating the alignment of training programs with industry demands.