Inspiration
As incoming grade 12 students, we recognize that some students may lack access to information about universities and matching their interests to university programs. Some students do not even know what programs they would want to go into. They might search the web for hours without finding anything useful, and they might even try to ask their guidance counselors for some advice without receiving any useful or valuable information other than "Go check the university website!" (so helpful!). Those guidance counselors could instead recommend their students to the CRED website for better insight into their future University plans.
What it does
CRED first asks about your grade and interests, and an AI then uses that information to provide suggestions of programs you can apply to, as well you with almost everything you would need to know about getting into those programs (required courses and averages, supplementary applications and interviews, and the like).
How we built it
Everything was coded using Visual Studios. For our frontend, we used Figma to draft our design for our webpage. And then we used our VERY VERY extensive knowledge of HTML and CSS to create a few drafts of our webpages until we got a look we were kind of okay with. For the backend, we coded the AI using Python and connected the frontend and backend using Flask.
Challenges we ran into
We ran into quite a few hurdles, most notably that none of us knew how to code using HTML, and only one of us knew Python. So after a few sped-up YouTube videos, we were able to learn HTML very speedily and to start using it for our frontend. Plus, we used some videos and ChatGPT to learn how to use Flask alongside Python to connect frontend and backend.
Accomplishments that we're proud of
We are very proud that we were even able to put out a website in such a short time. It isn't something any of us have done before, plus none of us even knew HTML or how to use Flask, so being able to create a functioning website with both those tools was very very satisfying.
What we learned
We learned a lot about APIs through the workshop, and connecting front-end and back-end with them. Most, if not all, of HTML, CSS, Flask, and coding for AI was new to us. This entire project was a learning experience, from learning to use VS code, to designing the front and back end, to using brand new languages and new Python libraries.
What's next for CRED
We want to efficiently implement machine learning into our system for it to be able to search the web with a lot more efficiency and rapidity. We also want to enable account log-in and personalization of the website, as well as potentially adding a quiz instead of a few easy questions to determine the best programs for the user. We will continue to polish the website to increase user interactivity and functionality. We will also increase the maintenance and security of our website, as well as improve its UI/UX.
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