Smart Skill Gap Analyzer for Career Readiness

Abstract: In the rapidly evolving global job market, students frequently encounter challenges in discerning the requisite skills for their desired career trajectories and accurately assessing their preparedness levels. This research introduces a Smart Skill Gap Analyzer for Career Readiness, an advanced artificial intelligence (AI)-based system designed to meticulously analyse a user’s existing skill set against the dynamic demands of a target job role. The system not only precisely identifies skill discrepancies but also forecasts the potential trajectory of skill improvement over time. Leveraging a real-time dataset meticulously curated from prominent online job portals, the system captures contemporary industry skill requirements. Machine learning models, specifically Linear Regression, Random Forest, and Logistic Regression, implemented using the Scikit-learn library, are employed to estimate skill progression and predict the temporal investment required to achieve optimal job readiness. Furthermore, the system incorporates a sophisticated resume analyser for automated skill extraction and a personalized learning recommendation module that suggests pertinent courses for targeted skill enhancement. An intuitive and interactive dashboard, enriched with Matplotlib and Plotly visualizations, empowers users to monitor their progress effectively and strategically plan their learning pathways. Future enhancements envision the integration of an AI chatbot career advisor to provide more dynamic and conversational guidance.

Keywords: Skill Gap Analysis, Career Readiness, Machine Learning, Artificial Intelligence, Linear Regression, Random Forest, Logistic Regression, Scikit-learn, Resume Analysis, Personalized Learning, Career Guidance.