Course-Recommendation-System

Link Of App Deployed on Heruko =- https://course-recommendation-systm.herokuapp.com/

Link of kaggle Dataset - https://www.kaggle.com/andrewmvd/udemy-courses

Introduction

In this Project The recommendation System was built for recommending online courses using Udemy Dataset

Process Workflow

• Dataset was read in pandas dataframe
• Data Cleaning and Preprocessing was done by Remove Stopwords Remove Special Characters Using Neattext library
• Vectorized our dataset with countvectorizer
• Cosine Similarity Matrix was Calculated for course Title
• course ID and Similarity Score was selected for recommendation
• Recommend The course

Link Of App Deployed on Heruko =- https://course-recommendation-systm.herokuapp.com/

EDA Was Done and following Key insights was seen:

• Courses with price of 20 has the highest sales
• Web Development Subject related courses was popular seen
• The courses Difficulty Level of 'All Level' was having highest number of subcribers
• Courses with price of 20 has the highest sales
• The most profitable course was ID : 625204 and Title : 'The Web Developer Bootcamp' with price 200 and Profit 24316800 cash.
• Year 2015 has highest number of subscriber and profit.

EDA Link - https://github.com/Siddhantjad/Course-Recommendation-System/blob/main/EDA.ipynb

Link Of App Deployed on Heruko =- https://course-recommendation-systm.herokuapp.com/