- 📘 Introduction
- 🔍 Fields of Study
- 📊 Course Levels
- 🔧 How to Use This Repository
- 🤝 Contributing
- 📄 License
This repository aims to be a one-stop resource for anyone looking to learn and advance their skills in various AI and data fields. Whether you're just starting out or looking to deepen your expertise, you'll find valuable resources here.
We cover the following fields in AI and data:
- Data Science 📊
- Data Analysis 📈
- Data Engineering 🏗️
- AI Engineering 🧠
- DevOps ⚙️
- Machine Learning Engineering 🤖
- Business Intelligence (BI) Analysis 📉
- Cloud Engineering ☁️
- Data Architecture 🏛️
- Robotics Engineering 🤖
Courses are classified into three levels to guide your learning path:
Courses and resources designed for individuals who are new to the field. These courses cover fundamental concepts and provide a solid foundation.
Courses and resources for individuals who have a basic understanding of the field and are looking to build on that knowledge. These courses cover more advanced topics and techniques.
Courses and resources for individuals who have a strong understanding of the field and are looking to specialize or deepen their expertise. These courses cover complex topics and advanced practices.
- Choose your level: Within each level, you'll find markdown files listing the courses and resources available.
- Access the resources: Each markdown file contains links and descriptions for the courses. Follow the links to start learning.
We welcome contributions from the community! If you have a course or resource you'd like to add, please follow these steps:
- Fork the repository.
- Add your course or resource to the appropriate level.
- Submit a pull request with a brief description of the addition.
This repository is licensed under the MIT License. See the LICENSE file for more details.
Happy Learning! 🎉