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Inspiration In STEM fields, women often face unique challenges, from limited mentorship opportunities to gaps in career advancement and salary equity. This project was inspired by the need to provide women in STEM with data-driven guidance and actionable insights to advance their careers effectively and equitably. By leveraging AI, this system provides personalized recommendations that support professional growth and promote leadership among women in technology.
What We Learned Throughout the development process, we learned the importance of creating user-centered prompts for AI-generated content, which requires balancing specificity with flexibility to yield accurate, useful responses. Additionally, working with career data highlighted the importance of data ethics and gender equity in AI-driven insights.
How We Built It This project uses Google’s Gemini API to generate personalized career paths, salary insights, and mentorship resources. Flask serves as the backend framework, handling API requests and managing session data, while Pandas processes any data manipulation. We designed the app to be secure, using secret key management for session handling.
Challenges Faced A key challenge was parsing and validating the JSON responses from the AI model. Since the responses sometimes deviated from the expected structure, we implemented error handling to ensure the responses were processed accurately. Additionally, we faced challenges in sourcing comprehensive salary data and providing equitable recommendations based on various user profiles.
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