UNSW AI RESUME ANALYZER AND COURSE RECOMMENDER

Receive personalised recommendations for electives based on your resume with just a click.

Comment

Inspiration

Students often have to manually search through MyPlan, the UNSW Handbook, and other university resources to figure out which courses will benefit their resume and be of their interest. We as a team find this process tedious and time consuming. We wanted a solution that could simplify elective selection while providing personalized recommendations based on a student's skills and experiences.

What it does

Our project analyzes a student's resume and recommends electives that will strengthen their academic profile. Now, instead of manually searching for courses, students can upload their resume and instantly receive a list of relevant electives tailored to their interests and skills.

How we built it

-We created a web interface where students can upload their resume as a PDF. The text is extracted from the PDF and converted into a JSON object. -The extracted resume data is sent to an AI model, which analyzes the content for skills, experiences, and academic interests. -We used DevSoc's API to retrieve information on all available electives and courses. -The AI model compares the student's profile with course information (stored in a CSV file) and recommends the most relevant electives. -To handle computationally intensive AI tasks, we implemented a system where resume data is sent from the user to a teammate’s more powerful PC for processing, and the results are sent back to the user seamlessly.

Challenges we ran into

  • we found that running the AI models on laptops took 30 mins due to insufficient computing power
  • we had to figure out a way to send a user's resume data to a teammate's PC, run the AI model on the PC and then send the results back
  • another issue was that, initially the user and the PC had to be on the same network. We had to figure out how to enable 100% functionality when the two are on different networks.
  • the final issue we faced was how to make this project accessible to anyone. In short, we had to figure out a way to deploy the project in a reliable manner. ## Accomplishments that we're proud of -Developed a modern, sleek front-end that is user-friendly and responsive. -Successfully implemented an AI model that provides personalised elective recommendations. -Created a system to connect any student's laptop to a more powerful server for AI processing. -Reduced the manual effort required to search for electives and provided a clear, actionable output for students. ## What we learned -How to use FastAPI to build APIs and link multiple devices for different tasks. -Techniques for extracting and processing text from PDF files using Python. -How to fine-tune AI models to provide accurate course recommendations. -The importance of designing a user-friendly interface while managing backend complexity ## What's next for UNSW AI RESUME ANALYZER
  • improving the accuracy of the AI model
  • strength and gap analysis after analysing the resume
  • elaborating on why the elective was recommended

Built With

Share this project:

Updates