CourseRecommendationSystem

This project aims to develop a personalized recommendation system for students seeking online courses and resources to enhance their learning experience. The system leverages a Coursera dataset from Kaggle and simulates user data to model realistic learning preferences. The system predicts course ratings tailored to individual users based on their educational background, preferences, and previous performance by employing Random Forest Regressor and content-based filtering techniques. This report provides an in-depth analysis of this system's methods, results, and implications, demonstrating its potential for scalability to various resource types, including videos, articles, books, and more.