C2W - Learning Platform with Artificial Intelligence

C2W is an innovative learning platform developed using the Flask framework and powered by Artificial Intelligence to provide a personalized and effective learning experience. This project was created as part of the Samsung Innovation Campus with the aim of transforming education using advanced technologies.

Table of Contents

• About the Project
• Features
• Requirements
• Installation
• Usage
• Contributing
• License
• Authors

About the Project

C2W (Class to World) is an online learning platform that uses Artificial Intelligence to adapt educational content according to the student's learning style. The platform allows for the creation of personalized courses that are continuously optimized based on students' performance and preferences using machine learning algorithms.

Technologies Used

• Programming Language: Python
• Framework: Flask
• Artificial Intelligence: [TensorFlow/PyTorch/OpenAI API/Other]
• Database: [SQLite/PostgreSQL/MySQL]
• Other Tools: Docker, Git

Features

• Personalized Courses: The platform adapts the content and difficulty of courses based on student progress.
• Artificial Intelligence: The system is powered by machine learning algorithms that recommend activities and content based on student behavior.
• Course Management: Creation, editing, and management of courses for various areas of knowledge.
• Progress Monitoring: Detailed reports on student performance, with insights generated by AI.

Requirements

Ensure you have the following requirements installed:

• Python 3.8 or higher
• Flask 2.0 or higher
• [AI Tool: TensorFlow/PyTorch]
• Docker (optional for deployment)
• PostgreSQL/MySQL (or another database)

Installation

1. Clone the repository:

   git clone https://github.com/allanlealluz/Projeto_Samsung

2. Navigate to the project directory:

   cd Projeto_Samsung

3. Create and activate the virtual environment:

   python3 -m venv venv
   source venv/bin/activate

4. Install the dependencies:

   pip install -r requirements.txt

5. Configure environment variables:

   cp .env.example .env
   # Edit the .env file as necessary

6. Run the project:

   flask run

Usage

After installation, access the platform at http://localhost:5000. Register and explore the available courses. The platform will monitor your progress and suggest new activities based on your performance.

Contributing

Contributions are welcome! To contribute:

1. Fork the repository.
2. Create a branch for your feature (git checkout -b feature/NewFeature).
3. Commit your changes (git commit -m 'Add NewFeature').
4. Push to the branch (git push origin feature/NewFeature).
5. Open a Pull Request.

License

This project is licensed under the MIT License.

Authors

• Allan Leal - Lead Developer - My LinkedIn

Acknowledgments

Thanks to the Samsung Innovation Campus for the opportunity to develop this project and gain knowledge in AI and software development.