A user-based Course Recommendation System is developed in this paper. The recommender system is constructed as an online website/application which is capable of producing a personalized list of courses which a user can take. Modern versions of traditional recommender system, such as collaborative filtering are considered to be efficient in this domain of user-based recommendation. On the basis of collaborative filtering principle, the recommendation process is divided into three steps, representation of student data, generation of neighbor user (student) and the generation of course recommendations. In order to compute the likenesses amid each user, the Cosine method is adopted during the process of the generation of neighbors. Then the course recommendations are generated according to the ratings of the other students and his personal ratings. © Springer Nature Singapore Pte Ltd. 2020.