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AI-Based Career Guidance System using Machine Learning

Dr. Y. Mohammed Iqbal1, A. Pravin2, Dr. S. Peerbasha3,Dr. M. Mohamed Surputheen4, Dr. M.
Rajakumar5
Department of Computer Science, Jamal Mohamed College, Affiliated to Bharathidasan University,
Tiruchirappalli, Tamil Nadu, India

Abstract- Choosing a suitable career has become increasingly challenging for students due to rapid technological advancements, diverse career options, and evolving skill requirements. Traditional career counseling methods often rely on manual evaluation and subjective judgment, making them time-consuming, less accurate, and difficult to scale. To address these limitations, this paper proposes an AI-based career guidance system that provides accurate and personalizedcareer recommendations using machine learning techniques. The proposed system analyzes students’ technical and soft skill profiles using a structured dataset and applies supervised learning models such as Random Forest,XGBoost, Support Vector Machine, Neural Network, and Logistic Regression. The models are evaluated using multiple train–testsplits toensure robustness. Experimental results demonstrate that machine learning models can effectively support career decision-making,with Support Vector Machine and Logistic Regression achieving superior performance. Overall, the systemoffers  a scalable, data-driven framework that can assiststudents and educational institutions in making informed career choices.
Keywords:Career guidance system,artificial intelligence, machine learning, supervised classification, student skill analysis, decision support system.