Skill Path AI

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  Skill Path AI

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  Skill Path AI Roadmap

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  Skill Path AI Tutorials

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  Skill Path AI Quiz Questions

Inspiration

The inspiration for SkillPath AI came from seeing how many students want to get good jobs but feel confused about which skills to learn and where to begin. We wanted to create a simple platform that helps students explore career paths, find learning resources, and practice skills step by step.

What it does

SkillPath AI helps students explore career paths, understand the skills they need, access learning resources, and practice Python through interactive quizzes with scores. It provides a simple starting point for students preparing for future job opportunities.

How we built it

We built SkillPath AI using HTML, CSS, JavaScript, Python, and Flask. HTML and CSS create the website structure and design, while JavaScript adds interactivity. Python with Flask handles the backend and career roadmap logic. We also developed a Python practice quiz that displays students' scores. We tested the prototype locally using VS Code and explored the OpenAI API as a potential foundation for future AI-powered features.

Challenges we ran into

One of our main challenges was turning a common student problem into a simple, useful working prototype. We had to connect the website's frontend with Python and Flask, organize career roadmaps, and make the Python quiz work correctly. As beginners, debugging errors and arranging the features clearly helped us improve our problem-solving and development skills. Integrating more personalized AI guidance remains a future challenge.

Accomplishments that we're proud of

Our biggest accomplishment was turning a student-focused idea into a working web prototype. We developed career roadmaps, learning resources, and an interactive Python quiz with score tracking. We also connected to the OpenAI API in a separate test, giving us a starting point for future AI integration. This project helped us gain practical experience in web development, Python, Flask, debugging, and building solutions to real student problems.

What we learned

Through building SkillPath AI, we learned how to combine HTML, CSS, JavaScript, Python, and Flask to create a web application. We improved our skills in debugging, connecting frontend and backend components, organizing career roadmaps, and building an interactive quiz. We also learned how to test the OpenAI API and identified opportunities to add personalized AI guidance in the future. Most importantly, we learned how to turn a real student problem into a practical prototype.

What's next for Skill Path AI

Our next step is to integrate the OpenAI API into SkillPath AI to provide personalized career guidance and learning recommendations. We plan to expand career roadmaps, add more programming quizzes, track student progress, and recommend learning resources based on each student's goals and skill level. Our long-term vision is to make career preparation simpler, more accessible, and more personalized for every student.

Built With

• css
• flask
• html
• javascript
• openai-api
• python
• visual-studio-code