This study introduces a system designed to support learning programming with artificial intelligence (AI) applications, aiming to personalize the learning path for university students. The system can comprehensively store and analyze each student's learning process to provide adaptive feedback and suggest resources tailored to individual needs. The system can intelligently analyze programming errors and offer accurate debugging suggestions by applying advanced AI models. This approach enables the creation of personalized learning pathways based on prior learning outcomes, aiming to improve learning efficiency, reduce stress when encountering errors, and enhance the overall quality of programming education for students. The system's effectiveness is evaluated through students' progress and satisfaction levels, thereby contributing to developing intelligent tutoring systems in higher education.