Machine Learning based MOOC Course Recommendation System

Authors

  • Mohammed Suhail Shaikh Dept. of Computer Engineering SIES Graduate School of Technology Navi Mumbai, India
  • Rishabh Nair Dept. of Computer Engineering SIES Graduate School of Technology Navi Mumbai, India
  • Mohammed Zafar Shaikh Shree Bhagubhai Mufatlal Polytechnic Mumbai, India
  • Asmatara Shaikh Associate Professor Parle Tilak Institute of Management Mumbai, India
  • Ujwala Ravale Assistant Professor SIES Graduate School of Technology Navi Mumbai, India

DOI:

https://doi.org/10.5281/zenodo.13623168

Keywords:

MOOC, E-content, online education

Abstract

The use of Massive Open Online Courses (MOOCs) by students to advance their knowledge and abilities has grown in popularity in the modern world. Students may find it challenging to select the best course for their needs due to the variety of online learning platforms and courses. In this project, we suggest a mechanism for recommending Mooc courses that will assist students in finding the most appropriate course for a certain subject. According to user reviews, the algorithm will trawl through different online learning sites and choose courses. To help students choose the best courses, the recommendation system will take into account variables including subject, level of difficulty, course length, and course rating. Students can save time and effort in looking for the appropriate information by utilizing this approach. The suggested system may be a useful resource for helping students choose top-notch courses that fit their learning goals.

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Published

2023-11-25

How to Cite

Shaikh, M. S., Nair, R., Shaikh, M. Z., Shaikh, A., & Ravale, U. (2023). Machine Learning based MOOC Course Recommendation System. International Journal of Science and Social Science Research, 1(3), 260–264. https://doi.org/10.5281/zenodo.13623168
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