Career Quest

Inspiration

Having grown up as a minority in Canada, I found the resources that are made available to minority students under financial duress difficult to find and rare. I realized too late that the varitety of scholarships available to high achieving, financially struggling students was vast; and as such for this hackathon, my group and I made it our mission to not only make these scholarships easier to find, but also provide a database of courses and dynamic career paths for them to follow. In the effort of providing a clear path for young aspiring students who are trying to make their way in the academic world.

What it does

Our app utilizes a customized AI, country of origin and prospective career choices in order to plan out a path from beginning to end, encompassing exhaustive lists of programs, universities, prerequisites, levels of education and job positions at different levels of experience; creating a timeline from beginning to end for the career path so that young aspiring Engineers, Artists, Politicians, and more can get an idea of the life cycle for their prospective aspirations.

We also provide an exhaustive list of over 27,000+ scholarships worldwide; complete with keyword search, and diversity filters (race, gender orientation, Household income, etc.). This way we can ensure that we strike two birds with one stone, by supporting marginalized communities and ensuring that we maintain a sustainable method of information, educational advice and encouraging the next generation of students to pursue higher education.

As Computer Science, Statistics, and Mathematics students we can appreciate the wide variety of open source education on the world wide web, whether it comes from stack overflow, coursera or more; not all forms of education are packaged in a pretty university. To our brethren in war torn, third world countries and in between, high level sources of education are not always readily available.

As such we took it upon ourselves to package a comprehensive list of over 3000 open source courses, ordered and complete with keyword search and filters for different levels of experience; available in a variety of languages. Just search your topic and we have it.

How we built it

We utilized numpy, pandas, beautiful soup, csv, urllib, webdriver, and pool for data/web scraping for our scholarship and course database.

We utilized streamlit, flask, HTML, css, and django, to develop our front-end.

We utilized pandas, numpy, google generative-ai by training a custom gemini api on our web scraped datasets; In order to provide custom career paths. We utilized pandas and numpy to handle data management of the both datasets.

Challenges we ran into

Dependancies on certain frameworks, and libraries caused version conflicts that were difficult to resolve and we fixed this by maintaining a standard of requirements (requirements.txt) and working in virtual environments.

We had time crunches in that half of our team had a term test October 5th at 1 pm. So we were working with half of the team most of the time.

Beautifying the front end was a real challenge while working in streamlit, due to the simplistics nature of the framework, but I think that we were able to hurdle this challenge by compensating in complexity and custom images.

Accomplishments that we're proud of

Gathering 27000+ scholarships, training a custom ML model on a comprehensive database of universities, compiling 3000+ open source courses

What we learned

We developed an intimate relationship of Github features and development, comprehensive knowledge of AI and model training, API use, Front-end Development, and more.