Inspiration

My experience as a freshmen when building the schedule and then actually experiencing it

What it does

reads your plain-English preferences, picks conflict-free course sections, and ranks them by your preferences (input through the website)

How we built it

Python and Gradio for the interface, with NVIDIA Nemotron handling preference parsing and schedule comparison.

Challenges we ran into

Getting the API for Nemotron, selecting a model that suits this task well, and using the API.

Accomplishments that we're proud of

Being able to complete this project, and actually getting it to work as this is my first experience.

What we learned

Debugging a LLM API, and using Gradio & Python to build website and interface. Honestly time management, how to pace and schedule a project like this.

What's next for Pitt Schedule Optimizer

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