StudyBuddy

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  the dashboard

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  example

Inspiration

Many students struggle to understand concepts outside the classroom, especially when studying independently without access to a tutor. Searching online often leads to overwhelming or inconsistent explanations that are not tailored to a specific subject. StudyBuddy was inspired by the need for a simple, always‑available learning companion that explains concepts clearly based on the subject a student is studying.

What it does

StudyBuddy is an AI‑powered study assistant that helps students understand academic concepts. Users select a subject such as Maths, Science, or History and ask a question related to that subject. The application then generates a clear, subject‑focused explanation to help the student learn and revise more effectively.

How we built it

We built StudyBuddy as a web application with a simple frontend and a backend API. The frontend was created using HTML, CSS, and JavaScript to allow users to select subjects and ask questions. The backend was built using Node.js and Express to handle requests and communicate with the AI model. We integrated the Gemini API to generate subject‑specific explanations, and the application was deployed to the cloud using Microsoft Azure to make it publicly accessible.

Challenges we ran into

One of the main challenges was working with AI API quotas and cloud access limitations during development. As beginners, setting up cloud services and managing API keys securely was also a learning curve. We had to carefully structure the application to separate frontend and backend logic and ensure that sensitive information was not exposed.

Accomplishments that we're proud of

We’re proud of successfully building a working AI‑powered application from scratch as beginners. Integrating an AI model into a real web app, structuring a proper backend, and deploying the project to the cloud were major milestones for us. We’re also proud that the app solves a real problem in a simple and user‑friendly way.

What we learned

Through this project, we learned how frontend and backend systems communicate, how APIs work, and how to integrate AI into applications responsibly. We also gained experience with cloud deployment, environment variables, and debugging real‑world issues such as quota limits and deployment errors.

What's next for StudyBuddy

In the future, we plan to add features such as practice questions, quizzes, and personalized study recommendations. We also want to include user accounts so students can save their learning history and track progress. Expanding subject coverage and improving explanation quality are also key next steps.

Built With

• css
• groq
• html
• javascript
• node.js