E-learning Video Recommendation System

Abstract

The E-Learning Video Recommendation System is a web application designed to simplify 
the search for relevant educational videos in the overwhelming digital space. It tackles the 
challenge of finding quality learning content efficiently by offering instant, personalized 
video suggestions based on user queries or topics. Built with Python, Flask, and integrated 
with the YouTube Data API via SerpApi, the system retrieves real-time video results. The 
frontend, developed using HTML, CSS3, and Tailwind CSS, ensures a responsive and 
user-friendly interface across devices. Without requiring registration, it provides quick 
access to curated academic and professional content. Through its modular design and 
real-time integration, the platform delivers scalable, up-to-date recommendations while 
paving the way for future personalization enhancements.