Inspiration

From Youtube's "up next" to Spotify's recommendations, our lives have been filled with AI powered ___. However, when it comes to our learning practices (arguably the most important aspect of our young lives) we seem to be stuck in the 18th Century! StudAI brings studying to the modern era with study partner matching, tutoring services and a revolutionary ML Study tracker, all to help you study smarter and not harder. StudAI. Give it a try!

What it does

StudAI is a web application and Chrome extension that makes studying a more enjoyable and productive experience. Based on your personality type and academic interest, StudAI uses the power of artificial intelligence to match you with other students that you can study together with. The Chrome extension also learns from your studying habits and lets you know when you should get back to studying and when it's time to take a break.

How we built it

The user interface was designed with Figma and built with React and Material UI. The backend API was built with Node and Express. The machine learning model to match users was built with Python and scikit-learn. Netlify was used to host the frontend and Heroku was used to host the backend API. CockroachDB was used as the database.

Challenges we ran into

As we all had little experience with machine learning and artificial intelligence, we faced challenges in creating the machine learning model. We also had little experience working with SQL and relational databases so using CockroachDB as our database was also somewhat of a challenge. Building a chrome extension was another thing with which we were unfamiliar and as such we faced difficulties in creating the extension.

Accomplishments that we're proud of

We are really proud to have brought so many technologies that were new to us together to create this project. Working on this project was a great learning experience for all of us.

What we learned

We learned to use machine learning models using the scikit-learn package. We also learned to work with relational databases and write SQL queries. We learned a lot about deployment with a hybrid cloud strategy, utilizing both Heroku and Netlify.

What's next for StudAI

In the future, we would like to add the ability to chat with and hold video call sessions with study partners. We would also like to build mobile applications so students can use StudAI on the go. Another feature that we would like to implement is matching students based on their location.

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