INTELLIGENT CAREER RECOMMENDATION SYSTEM USING MACHINE LEARNING

A person's choice of career has a significant impact on both their professional development and level of personal fulfillment.Conventional career counseling techniques are frequently manual, arbitrary, and have a narrow focus.Intelligent algorithms can now evaluate student data and offer tailored career recommendations thanks to the development of machine learning (ML).In this paper, supervised machine learning methods including Random Forest, Decision Tree, Support Vector Machine (SVM), and Artificial Neural Networks (ANN) are used to propose an Intelligent Career Recommendation System (ICRS).To anticipate appropriate job domains, the approach examines personality factors, aptitude scores, skill sets, and academic performance.The Random Forest algorithm obtained the maximum accuracy of 91.4%, according to experimental data.The suggested system encourages data-driven decision-making in educational institutions and lessens career mismatch.