Coursera-REC: Explainable MOOCs Course Recommendation using RAG-facilitated LLMs

Coursera-REC is a Large Language Model-based course recommendation system designed to enhance MOOC learning experiences by tailoring recommendations to user-specific goals and preferences. Utilizing Retrieval-Augmented Generation (RAG), it retrieves contextual data from a comprehensive knowledge base to offer clear, reasoned course suggestions. This approach could effectively address the 'cold-start' problem by using rich contextual information, enabling the generation of meaningful initial recommendations for new users. Coursera-REC's flexible prompt template allows for customized development, ensuring that the system's output can be tailored to better suit individual user needs. This design showcases the potential of a scalable, adaptable course recommender system, setting it apart in the evolving landscape of online education.