LearnSync: Navigating Learning Opportunities
Anushka Ashok Pote, Ashish Ruke, Suvarna Abhijit Patil, Reena Shrikant Sahane · 2024
Course recommendation systems are tools designed to suggest relevant courses to users, based on their interests and previous interactions. These systems play a crucial role in providing personalized learning experiences and guiding users toward courses that align with their goals. The inclusion of the NIRF rating enables informed reliance on colleges and universities to be made. A user interactive chatbot is designed to reduce customer service time and effort for users by providing them with instant help and advice. Students follow up with the progress of the educational field with news-worthy events such as topical courses and knowledge that direct continuous learning. All these have been integrated in single project work by using flask (python) in the backend and HTML and CSS in frontend. Various ML algorithms, such as K-means clustering for prediction, Random Forest Regression for NIRF ranking, and WordNetLemmatizer for interactive chatbot, are used to build this project. Accuracy of all these models lies between 84%–89%. News API is used for fetching all news from worldwide related to the educational field. Various data sets have been used to train different models. Overall project is designed similarly to other learning platforms such as Byju’s, Unacademy, and many more.