PERSONALIZED E - LEARNING COURSE RECOMMENDATION SYSTEM

Abstract

The rapid growth of online education platforms has created an overwhelming number of learning resources, making it difficult for learners to identify courses that align with their interests, skill levels, and career goals. This project proposes a Personalized E-Learning Course Recommendation System that leverages Machine Learning (ML) and data-driven techniques to provide customized course suggestions for individual users. The system aims to enhance the learning experience by analyzing user behavior, preferences, past learning history, and performance to deliver relevant and adaptive recommendations. The proposed system utilizes techniques such as collaborative filtering, content-based filtering, and hybrid recommendation approaches to generate accurate suggestions. User data, including course interactions, ratings, and completion history, is collected and preprocessed to extract meaningful features. The system then applies similarity measures and predictive models to identify courses that best match the user’s profile. Additionally, Natural Language Processing (NLP) techniques can be used to analyze course descriptions and user feedback, further improving recommendation accuracy. The system continuously learns from user interactions, enabling dynamic updates and improved personalization over time. The performance of the recommendation system is evaluated using metrics such as precision, recall, and recommendation accuracy. Experimental results demonstrate that the system effectively identifies relevant courses, improves user engagement, and enhances learning outcomes. The system can be integrated into existing e-learning platforms or deployed as a standalone application, providing users with an intelligent and user-friendly interface. Overall, this project highlights the importance of personalized learning and demonstrates how MLbased recommendation systems can transform digital education by delivering tailored learning experiences and supporting continuous skill development.