Reflective Career Advisor

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  First User Page

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  Results Page

Reflective Career Advisor is a web application that guides users through selecting a faculty and subject, answering relatable questions, and receiving personalized career recommendations. It highlights essential skills, industry-relevant certifications, salary ranges, and practical next steps — all while encouraging thoughtful self-assessment.

We built the project using Python and Flask for the backend, HTML and CSS for the frontend, and Chart.js for visualizing recommendations. The scoring logic matches user responses to industry-relevant job roles, then generates tailored insights based on their answers. The app was deployed publicly using Render and GitHub.

One major challenge was designing questions that meaningfully differentiate career paths while remaining simple and relatable. Another challenge was structuring the scoring system so recommendations felt logical and accurate. Deployment issues and route handling also required debugging and adjustments.

We’re proud that the project feels clean, structured, and practical. It doesn’t just recommend jobs, it explains why they fit, suggests certifications, and provides realistic salary ranges. We also successfully deployed it publicly, making it accessible beyond the hackathon environment.

We learned how to design decision logic, structure a Flask application, improve UI/UX consistency, and debug real deployment issues. We also gained a deeper understanding of how important clarity, structure, and user experience are in building meaningful tools.

Next, we plan to integrate AI-generated personalized reflections, expand career databases with regional data, add resume-building suggestions, and refine the analytics behind skill mapping. We also want to improve accessibility and add user accounts to track growth over time.

Built With

• chart.js
• css
• flask
• html
• python