DSSL: A Comprehensive Analysis of Optimizing Professional Competence through Deep SkillSetLearn Model for Soft Skills Training

Soft skills are crucial for employability because they complement technical expertise and contribute to a well-rounded, adaptable, and effective professional. This study delves into the intricate realm of professional competence optimization through the innovative Deep SkillSetLearn (DSSL) Model, specifically designed for Soft Skills Training. The research provides a comprehensive examination of the model, showcasing its prowess in integrating advanced technologies such as Cascaded DenseNet and ZFNet Model. The amalgamation of these cutting-edge architectures within DSSL promises a refined and effective approach to cultivating essential soft skills among individuals. Notably, the proposed DSSL Model exhibits an impressive accuracy of 97%, underscoring its proficiency in accurately identifying and analyzing various soft skills attributes. Through an in-depth analysis, this abstract aims to shed light on the intricacies of DSSL's architecture, highlighting its potential to revolutionize the landscape of soft skills training for enhanced professional competence and employability. The model's exceptional accuracy further emphasizes its utility as a robust tool for accurately assessing and enhancing soft skills, contributing significantly to the overarching goal of preparing individuals for the dynamic demands of the modern professional landscape.