A Comprehensive Survey on Machine Learning Approaches in Course Recommendation System

There is a plethora of online platforms that offer courses, making the course recommendation a difficult assignment in online learning. The student has the important responsibility of selecting the most suitable course from the available options. As a result, our study incorporates a number of machine learning techniques that were employed to propose the course based on a multitude of criteria, including user preferences, historical data, ratings, and more. Many machine learning methods, such as Collaborative, Content-Based, and Hybrid Filtering, make recommendations easier. In order to improve accuracy and provide the best recommendations, successful course recommendation systems frequently use a combination of these approaches. In the end, we want our research to provide a comprehensive review of machine learning recommendation approaches and to build an educational platform that allows students to choose the ideal course for their needs while also making high-quality learning materials available to students all around the world.