Authors: Rushikesh Falke, Vishal Bagal, Pranav Bartakke
Abstract: Choosing the right career path is a critical decision for students and often requires personalized guidance based on their interests, skills, and abilities. This paper proposes an Intelligent Questionnaire-Based Career Path Recommendation System that utilizes the Random Forest machine learning algorithm to recommend suitable career options. The system collects user responses through a structured questionnaire covering personality traits, technical skills, academic interests, aptitude, and career preferences. The collected data are processed and analyzed using a trained Random Forest model to predict the most appropriate career path. In addition to career recommendations, the system provides guidance on relevant skills and learning resources to enhance career readiness. A web-based interface enables users to complete the assessment and receive recommendations instantly. The proposed approach improves the accuracy and personalization of career guidance compared with traditional counseling methods. The experimental results demonstrate that the system provides reliable recommendations and supports students in making informed career decisions. The proposed framework is scalable and can be extended with real-time job market data and advanced AI techniques in future work.
