DESIGN AND IMPLEMENTATION OF THE COURSE REMINDER SYSTEM
Abstract
This project presents the design and implementation of a Course Recommender System tailored for higher education institutions. The system aims to assist students in selecting suitable courses by
analyzing their academic history, program requirements, and personal learning preferences. Using a combination of content-based filtering and collaborative filtering techniques, the system generates
personalized course recommendations that align with each student’s academic goals and interests. A
user-friendly interface allows students to input preferences, view recommended courses, and explore detailed course information. The system’s architecture integrates a structured database, a
recommendation engine, and a responsive front-end to ensure efficient performance and ease of use. Results from testing indicate that the recommender system enhances decision-making, reduces course selection uncertainty, and supports a more informed and personalized academic planning process. This project demonstrates how intelligent systems can improve student engagement and academic success in higher education.
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