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🎓 COURSES Repository

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This repository contains comprehensive course materials and resources from various prestigious institutions and platforms, focusing on Robotics, Computer Vision, Deep Learning, and AI technologies.

📚 Course Collection

1. Aerial Robotics - University of Pennsylvania

  • Advanced concepts in aerial robotics
  • Drone programming and control systems
  • Flight dynamics and navigation

2. Deep Learning and Data Science Course - Dunup

  • Fundamentals of Deep Learning
  • Data Science principles and applications
  • Practical implementations and case studies

3. Introduction to Computer Vision and Image Processing - IBM

  • Image processing fundamentals
  • Computer vision algorithms
  • OpenCV implementations
  • Real-world applications

4. Neural Networks and Deep Learning Course - University of Tehran

  • Neural network architectures
  • Deep learning frameworks
  • Practical implementations
  • Advanced optimization techniques

5. TensorFlow Advanced Techniques Specialization - DeepLearning.ai

  • Custom layers and models
  • Advanced TensorFlow features
  • Model optimization
  • Custom training loops

6. Jetson Nano B01 Boot Camp 2021 - Udemy

  • NVIDIA Jetson Nano programming
  • Edge AI implementation
  • Embedded systems development

🚀 Getting Started

  1. Clone the repository:
git clone https://github.com/Awrsha/COURSES.git

📂 Repository Structure

COURSES/
├── Aerial-Robotics/
├── DL-and-DS-Course/
├── Computer-Vision-IBM/
├── NNDL-Course/
├── TensorFlow-Advanced/
└── Jetson-Nano-Bootcamp/

🔧 Prerequisites

  • Python 3.7+
  • TensorFlow 2.x
  • OpenCV
  • CUDA (for GPU acceleration)
  • Jupyter Notebook

💡 Key Features

  • Comprehensive course materials
  • Practical examples and implementations
  • Hands-on projects
  • Assessment materials
  • Reference documentation

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

👤 Author

Arsha

🌟 Acknowledgments

  • University of Pennsylvania
  • IBM
  • DeepLearning.ai
  • University of Tehran
  • Dunup
  • Udemy

📞 Contact

For any questions or concerns, please open an issue or contact the repository owner.

⭐️ If you find this repository helpful, please consider giving it a star!