EduNexus: A Personalized Course Recommendation System Based on Skills and Career Interests

• Author(s): Bhakti Sable ; Neha Bhadale ; Vaishnavi Pawar ; Sagar Deshmukh ; Asst. Prof. Rutuja Kulkarni
• Paper ID: 1704432
• Page: 330-333
• Published Date: 13-05-2023
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 6 Issue 11 May-2023

Abstract

With the growth of online learning platforms, students now have access to a wide choice of courses on a wide range of topics. For students, the sheer quantity of possibilities can be daunting, and selecting the correct course can be difficult. Learners spend endless hours exploring each of the online course platforms in order to find the course that best fits their interests. Finding courses that are a suitable fit for their interests and learning goals can thus be made easier for students by employing customised course recommendations. The proposed system is intended to provide users with tailored course recommendations based on their interests, skill sets, and personal preferences. Our approach in this study uses machine learning methods to provide meaningful cross-platform course recommendations.

Keywords

Recommendation system, Machine learning, Feature extraction, Data Mining, Cosine similarity

Citations

IRE Journals:
Bhakti Sable , Neha Bhadale , Vaishnavi Pawar , Sagar Deshmukh , Asst. Prof. Rutuja Kulkarni "EduNexus: A Personalized Course Recommendation System Based on Skills and Career Interests" Iconic Research And Engineering Journals Volume 6 Issue 11 2023 Page 330-333

IEEE:
Bhakti Sable , Neha Bhadale , Vaishnavi Pawar , Sagar Deshmukh , Asst. Prof. Rutuja Kulkarni "EduNexus: A Personalized Course Recommendation System Based on Skills and Career Interests" Iconic Research And Engineering Journals, 6(11)