Inspiration
As students, we discussed the biggest problem we face during self‑studying. We realized that many of us struggle not because we lack effort, but because we lack a clear and reliable structure of our courses.
Although platforms like Knowunity already provide useful notes and resources, they mainly focus on content sharing rather than helping students build a systematic understanding of the overall course structure.
What it does
Students first choose their university and the courses they are currently taking. Based on this information, our system extracts structured data from the DiscoverUni dataset and generates a customized knowledge map for the selected course.
Once generated, the knowledge map also possesses quizzing features, PDF upload and progress tracking.
How we built it
A structured backend using Django for HTTP requests to communicate with the front end.
The backend processes the university and course name inputted by the user, processes this data using Gemini to find the modules for the users' course.
After loading the modules, the backend generates an adjacency matrix used by the front end to create a graph data structure, the knowledge map.
Challenges we ran into
Finding a suitable dataset that could map university courses to their modules & accurately storing this data.
Dealing with HTTP requests and debugging using status codes.
Accomplishments that we're proud of
Successfully deploying the application.
Turning two simple parameters, University name & course name, into a useful product for a student.
What we learned
How to use the Django framework
How to use Gemini as an API within the project.
What's next for UniMap
Partnership with universities to facilitate data accuracy resulting in a more reliable map structure, as well as increasing adherence of students.
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