Update README.md

README.md

-# GWData-Bootcamp
-Gravitational Wave Data Exploration: A Practical Training in Programming and Analysis
+# 引力波数据探索：编程与分析实战训练营
+# Gravitational Wave Data Exploration: A Practical Training in Programming and Analysis
+
+> Under construction...
+
+Welcome to the GitHub repository for the Gravitational Wave Data Exploration Bootcamp Series! 
+This course is meticulously designed to provide a solid foundation in programming, operational knowledge, and data-driven modeling skills centered around gravitational wave data analysis and research.
+
+## Training Objectives
+- Equip participants with robust programming and operational skills, and foundational training in data-driven modeling, focusing on gravitational wave data analysis and related research areas.
+- Discuss the common research methodologies combining gravitational wave data processing with AI technologies, with hands-on examples and projects for practical understanding and mastery.
+- Analyze cutting-edge deep learning models and apply them to real-world gravitational wave data analysis problems through specific case studies.
+
+## Target Audience
+- Undergraduate and graduate students interested in data analysis and algorithm development, especially those focusing on gravitational wave data processing and related research.
+- The course also welcomes undergraduates with a basic programming background, looking to enhance their data analysis skills or with an interest in gravitational wave data processing.
+- Future professionals aspiring to work in space-based gravitational wave detection projects and related research fields.
+
+## Course Design Philosophy
+- Drawing from past teaching experiences and identified knowledge gaps in student research projects, the course introduces relevant concepts and common methods to ensure comprehensive understanding and application in research.
+- The course is scheduled weekly or bi-weekly, each session lasting about 3 hours, combining online and offline methods (腾讯会议) to ensure interactivity and practicality.
+- The curriculum is expected to be offered once per semester or annually, with continual updates and enrichment based on student feedback and research demands.
+
+## Course Outline
+- **Part Zero**: Motivational Introduction
+  - Slide, Video
+- **Part One**: Programming Development Environment and Workflow
+  - Linux Commands and Shell Scripting
+  - Git Version Control (GitHub / GitLab)
+  - SSH Remote Server Access (Shell / VSCode)
+  - Containerization with Docker
+  - Hands-On: Setting up Python / Jupyter Development Environment
+  - Hands-On: Compiling LALsuite / LISAcode Source Code
+
+- **Part Two**: Python-Based Data Analysis Fundamentals
+  - Introduction to Python Programming
+  - Algorithms with Numpy / Pandas / Scipy
+  - Hands-On: Exploratory Data Analysis of GW Event Catalog / Glitch Data
+  - Hands-On: Matched Filtering for GW150914 Data
+  - Data Visualization in Python: Theory and Practice
+  - Hands-On: Reproducing Figures from GWTC Papers
+
+- **Part Three**: Basics of Machine Learning
+  - Overview of Artificial Intelligence
+  - Definitions, Objectives, and Types of Machine Learning
+  - Machine Learning Project Development and Preparation
+  - Hands-On: Clustering Analysis of LIGO's Glitch Data
+
+- **Part Four**: Introduction to Deep Learning
+  - Overview of Deep Learning Technologies
+  - Fundamentals of Artificial Neural Networks (ANN)
+  - Convolutional Neural Networks (CNN)
+  - Hands-On: Identifying Gravitational Waves from Binary Black Hole Systems using CNN
+  - Frontiers of Gravitational Wave Data Analysis and AI
+
+## Collaborating Institutions
+- University of Chinese Academy of Sciences (UCAS)
+- International Centre for Theoretical Physics Asia-Pacific (ICTP-AP)
+- Taiji Laboratory for Gravitational Wave Universe
+
+## Getting Started
+To participate in this course:
+
+1. Clone the repository:
+   ```bash
+   git clone https://github.com/iphysresearch/GWData-Bootcamp.git
+   ```
+
+(Under construction)
+
+## Contributing
+
+We welcome contributions to enhance course materials. Please fork the repository, make your changes, and submit a pull request.
+
+- Staff: This class is co-taught by [He Wang](https://iphysresearch.github.io/blog/) and (appending),
+- Questions: Email us at [taiji@ucas.ac.cn](mailto:taiji@ucas.ac.cn)
+
+## License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+
+## Acknowledgments
+
+- Contributions from the open-source gravitational wave community.
+- Educational resources and datasets from renowned institutions and projects in the field.
+