: In the digital world of online information huge amounts of Massive Open Online Courses (MOOCs) are available of
different category and domain. Multiple online courses are available on different platform finding appropriate course from this
massive available course is difficult for students. Recommender system plays vital role in finding appropriate courses to students.
Managing massive amount of information and identifying individual users’ choice and behavior has become tedious task
nowadays, so the aim of recommender system is to suggest relevant course to student based on user behavior and similarity with
another course. Several recommender system techniques are being implemented like content based, collaborative, Knowledge
based. This paper aims to build a hybrid approach using collaborative filtering with content base filtering. This system
recommendation is based on course description and ratings. Experiments were conducted on real datasets to get the overall
performance of proposed system.
