Q0 | Devpost

Interface

Inspiration

The nature of work has changed dramatically in the recent decades. Knowledge work is now the most valuable form of labour. Due to the increasing value of knowledge work, learning is becoming more fundamental to our future value creation.

Currently, software provides the most scalable way of learning but the focus is on content production and distribution of said content. Nowadays, Most universities publish courses online, and the number of creators who publish ed content has risen drastically in the recent years.

However, learners are overwhelmed with the amount of choices available and often they do not even know where to begin.

What it does

Q0 is an adaptive online learning tool designed to curate tailored course plans for individuals seeking to learn a new skill. As opposed to traditional MOOCs which generally provide a fixed learning track, Q0 personalises each user's learning map based on their background and current skill level, allowing them to learn much more effectively. Q0 leverages the vast array of high-quality online resources that are rapidly being created to ensure that the most up-to-date content is curated, saving users the significant time and effort which usually goes into manually curating online learning resources.

How we built it

The minimum viable product was developed in Python using Streamlit for the front-end interface. The backend uses a combination of our own algorithms for building and personalising study maps, as well as youtube and openAI APIs to search for the most relevant content to provide users.

Challenges we ran into

Actual implementation of the algorithm for hierarchical graph clustering and hypernym detection, graph-based recommendation algorithm

Accomplishments that we're proud of

Working Platform MVP

What we learned

Good things take time

What's next for Q0

Update the interface to make it more user-friendly Try different approaches for the actual implementation Use crowdsourcing to improve recommendation relevance