Throughout the pandemic, we as students struggled with online lectures as our medium of learning was snatched away from us. Our professors expected us to pay attention to online lectures and with all our sincerity we tried our best initially. But the learning environment never felt the same with family members constantly disturbing you with household chores. Eventually we started giving up. The pace of online lectures did not match our daily schedule. But in this darkness, we found the streetlight our fathers talked about. Websites like Udemy and Coursera helped us learn throughout the pandemic with Coursera even providing free courses without certifications. With the internet access with us always, we could learn at our own pace. While exploring these websites and learning the essentials of data science, I came across a method through which anyone can teach on these websites. But these courses even if not trending were expensive. Clearly there was a gap in understanding the consumers. Here I thought about my capstone idea. Why not develop a tool for teachers on these websites which can help predict the price range of their courses using data science?
The main aim of this project was to understand the consumer behaviour on websites that provide online courses which could be done by analysing the data. At the same time, I wanted to use that data to develop my tool. So, I had to collect the data accordingly. We used a google form which has been linked in our website to collect data from users.
The pdf is the final report submitted after making this project.
The ipynb file has the tool development code and model building.
The html files contain the website.