EduStream 📚💻

EduStream is a personalized learning platform designed to provide free and affordable educational resources to underserved communities. The application leverages AI to recommend customized learning paths based on user preferences.

📋 Table of Contents

1. Features
2. Demo
3. Installation
4. Usage
5. Contributing
6. Additional Notes

✨ Features

• Personalized Learning Paths: Get course recommendations tailored to your learning style and preferences.
• Interactive Tutorials: Access a variety of tutorials across multiple subjects.
• Quizzes and Forums: Test your knowledge with quizzes and engage with peers in forums.
• AI-Powered Recommendations: Use machine learning to generate personalized learning recommendations.

🌐 Demo

Check out the live demo of EduStream here.

🛠️ Installation

To run EduStream locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/Heet852003/EduStream.git
   cd EduStream

2. Set up a virtual environment (optional but recommended):

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Run the application:

   streamlit run app.py

🚀 Usage

After starting the application, open your web browser and navigate to http://localhost:8501. You will see the EduStream homepage where you can:

• Use the sidebar to navigate between Tutorials, Quizzes, Forums, and Personalized Learning.
• Select "Personalized Learning" to view AI-generated recommendations tailored to your preferences.

🤝 Contributing

We welcome contributions to EduStream! To contribute, please follow these steps:

1. Fork the repository.

2. Create a new branch for your feature or bugfix:

   git checkout -b feature/your-feature-name

3. Commit your changes with a clear message:

   git commit -m "Add new feature: your-feature-name"

4. Push to your forked repository:

   git push origin feature/your-feature-name

5. Create a Pull Request from your branch into the main repository.

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📌 Additional Notes

• Clearing Cache: If you encounter issues with outdated data, you can clear the Streamlit cache by running streamlit cache clear or by using the "Clear cache" button in the Streamlit app settings.
• Custom CSS and Images: Ensure that the static/css/styles.css and static/images/logo.png files are correctly placed in the static directory. You may customize these files to suit your needs.
• AI Recommender: The AI recommender logic is found in ai/recommender.py. You can adjust the recommendation engine by modifying this file.

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Thank you for using EduStream! We hope this platform enhances your learning experience. 🎓🌟