Inspiration
Career Granny fills a crucial gap in education by addressing the often-overlooked area of counseling. With the rapid growth of the computer science industry, students are overwhelmed by the vast array of career choices and the skills required. However, over 50% of American school counselors and teachers lack the specific knowledge to guide students in this field. Career Granny aims to empower students by helping them navigate this complex landscape and make informed career decisions for free.
What it does
Career Granny helps novice users discover potential careers by entering a simple keyword or career name. It suggests a career, identifies the five most important skills and proficiencies they need, and provides learning methods along with free resources for each skill. Users can explore hundreds of career options and select one that aligns with their interests and strengths. For students who already know their strongest skills, Career Granny predicts a suitable future career and offers additional resources to further develop the required skills.
How we built it
Career Granny was built using synthetically generated data, based on a large list of computer science careers and related skills. A dataset was created with proficiencies for various skills as columns and the corresponding career as the last column. A decision tree model was trained on this data, achieving about 85% accuracy. The entire project is coded in Python, using Streamlit for the interface, and is deployed on Azure for easy browser access.
Challenges we ran into
Generating a dataset with accurate data that reflected the most important skills for each career was tricky as I needed to manually generate a long list of careers and skills and then design the best algorithm to assign realistic skill proficiencies according to the corresponding career. It was also hard to decide what features to display in the app and which user interface would be easy to use but also powerful.
Accomplishments that we're proud of
Career Granny is fully functioning and deployed which is a big achievement as it makes it much easier for people without technical background to use. I am also proud that the app can take large amounts of data and produce high-accuracy results.
What we learned
I have learned how to design algorithms that minimize computing, make a clean user interface, and generate data in Python quickly and efficiently.
What's next for Career Granny
I plan to add more features, including recommended skill paths, detailed career information like incomes and work hours, and college guidance based on student results. I also want to create a student advice blog with insights from users about their own college or career journeys. Most importantly, I aim to spread Career Granny in my community to empower students to be career-ready.
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