International Journal of Scientific Research and Engineering Development

For many students, selecting a career in the Information Technology (IT) field can be very challenging considering the variety of career paths available. The proposed project will create an AI-Driven Career Recommendation and Personalized Learning System that will allow students to discover appropriate career options in IT based on their assessment results, interest and capability levels. Students will be evaluated on Theory, Practical, Aptitude and Communication assessments to determine their proficiency level as either Beginner, Intermediate, Advanced or Expert. A XGBoost based machine learning model will provide recommendations for careers within various areas of IT including; Python Programming, Java Programming, Web Development, Artificial Intelligence, Cybersecurity, Cloud Computing, Database Management Systems and UI/UX Designer. In addition to providing a career recommendation, the AI-Driven Career Recommendation and Personalized Learning System will provide students with materials that will enable them to advance within their chosen career path by providing a basic career roadmap, links to online resources, resume keywords, interview preparation materials, and potential project ideas. In addition, there will be a chatbot powered by AI to provide guidance for students on careers and training needs related to careers in IT. Overall, the proposed AI-Driven Career Recommendation and Personalized Learning System will provide students with the resources necessary to make educated decisions about their future careers in IT.

P.Rajapandian, V.Hemasree,"AI-Driven Career Recommendation and Personalized Learning System" International Journal of Scientific Research and Engineering Development, V9(3): Page(1601-1608) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.