The inspiration behind the Career Picker application was to provide users with a streamlined and personalized approach to exploring career options in the field of computer science. We wanted to create a tool that could help individuals make informed decisions about their career paths based on their preferences, skills, and interests.

What it does

Career Picker is an interactive web application that guides users through a series of questions related to their interests, skills, and desired work environment. Based on the user's responses to multiple questions, the application analyzes the input and suggests potential career options within the computer science field that align with their preferences.

How we built it

We built Career Picker using a combination of technologies. The front end of the application was developed using HTML, CSS, and JavaScript to create an intuitive and user-friendly interface. The backend is built using Python. We used Flask to create a web application and then used machine learning tools such as pandas, scikit-learn to handle the data. We trained the data through google colab.

Challenges we ran into

One challenge we ran into was the generation of ideas. We weren't sure which idea to go with at the start. After we started the project, some challenges we ran into were finding data, training the model, cleaning the data, and then bridging the front end to the back end.

Accomplishments that we're proud of

We are proud of successfully building an interactive and user-centric application that assists individuals in exploring career opportunities in the computer science field.

What we learned

We learned how to work with scikit-learn and use machine learning to set up algorithms to take in user's input and personalize a computer science career that fits them.

What's next for Career Picker

The next idea for Career Picker would be to connect front end and back end successfully, and then make the quiz more generalized for more career fields.

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