McSkill

McGill Skill Swap: Elevate your learning journey by exchanging skills with fellow students. Unleash your potential, and empower the community!

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Inspiration

Our inspiration stemmed from recognizing the diverse talents within the McGill student community and the untapped potential for peer-to-peer skill exchange. With new issues such as tuition hikes and elevated cost of living, we understand the financial burden placed on students may impede the opportunity to explore passions, hobbies, and helpful resources essential for individual success. Our platform allows the opportunity for students to connect and explore passions without any financial strain.

What it does

McSkill facilitates skill swapping among McGill students, enabling them to learn from each other and expand their abilities across various domains. By filling out an easy-to-use questionnaire, students can connect directly without any hassle.

How we built it

We built McSkill using a combination of web development technologies, including HTML, CSS, JavaScript, and backend frameworks like Node.js. We also integrated user authentication and database management systems for a seamless user experience.

Challenges we ran into

Our main challenges included designing an intuitive user interface, ensuring data security, and implementing efficient algorithms for matching users based on their skill preferences and availability.

Accomplishments that we're proud of

We're proud to have created a platform that fosters a culture of collaboration and continuous learning within the McGill community. Seeing students engage and exchange skills validates our efforts.

What we learned

Through McSkill, we learned the importance of user feedback, iterative design, and robust backend architecture. We also gained insights into community-building strategies and effective communication channels.

What's next for McSkill

Moving forward, we aim to expand McSkill's user base, enhance its features based on user feedback, and explore partnerships with student organizations and faculty members to enrich the skill-sharing experience. Additionally, we plan to integrate machine learning algorithms for better skill matching and personalized recommendations.

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