A mentorship platform that connects mentors and mentees for social good initiatives, powered by OpenAI, Ruby On Rails, and React.
Welcome to the Mentorship Platform, a project developed for the Women Who Code Hackathon for Social Good. This platform brings together mentors and mentees who share an interest in social good initiatives. It utilizes state-of-the-art technologies, including OpenAI for mentor avatar chatbots, Ruby On Rails for the backend, and React for the frontend.
The Mentorship Platform is a web-based application designed to facilitate mentorship and knowledge-sharing in the context of social good initiatives. Mentors and mentees can create profiles, specify their interests, and engage in meaningful conversations. The platform's AI matching tool ensures efficient pairing of mentors and mentees with shared interests, enhancing the overall mentorship experience.
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Profile Creation: Users can register and create detailed profiles, highlighting their areas of interest and expertise.
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AI Chatbot: We've integrated OpenAI's chatbot technology to provide mentor avatars that assist and guide mentees throughout their journey.
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Efficient Matching: Our AI matching tool uses machine learning to pair mentees with mentors who share similar interests and goals.
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Real-time Chat: Users can engage in real-time chat sessions, enabling effective communication and knowledge-sharing.
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Dashboard: Users have access to personalized dashboards, where they can monitor their mentorship engagements, find new mentors, and explore soft skills challenges.
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Social Good Projects: Our platform offers opportunities for users to get involved in social good projects, fostering positive social impact.
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Learning Communities: Mentees can form learning communities with other like-minded individuals to enhance their knowledge and skills.
Our Mentorship Platform leverages several technologies to deliver a seamless user experience:
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OpenAI: We use OpenAI's chatbot technology to power mentor avatars and provide AI-guided mentorship.
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Ruby On Rails: The backend of our platform is built using Ruby On Rails, which offers robust server-side capabilities and data management.
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React: For the frontend, we've employed React to create a dynamic and responsive user interface.
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Machine Learning: Machine learning algorithms are employed to optimize mentor-mentee pairing, enhancing the user experience.