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https://github.com/elcarrillo/computational_bootcamp_material

Material for a Computational Bootcamp
https://github.com/elcarrillo/computational_bootcamp_material

bootcamp-project computational-physics data-analysis data-visualization jupyter-notebooks

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Material for a Computational Bootcamp

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README 

        

## Repository for Computational Bootcamp Material 



![Bootcamp Image](images/stock_image.jpg)



This repository contains the course outline and related materials for a comprehensive multi-day course on various technologies and computational tools. The course covers topics from basic data management/manipulation and version control to advanced Python programming and visualization. In addition, this repository includes Jupyter Notebooks that provide hands-on exercises and projects for the Python portion of the course.



This bootcamp material is based on Software Carpentry principles: [Software Carpentry](https://software-carpentry.org/).



You can explore sample usage of this material on the following website: [Bridge Computational Bootcamp](https://elcarrillo.github.io/2023-08-01-bridge_computational_bootcamp/).



## Suggeted Course Outline and Contents



- [Setup and Introduction](#setup-and-introduction)

- [Data Management](#data-management)

- [General Commands and Environment Setup](#general-commands-and-environment-setup)

- [Python Basics](#python-basics)

- [Math, Numpy, Pandas, and Matplotlib](#math-numpy-pandas-and-matplotlib)

- [Git and GitHub](#git-and-github)

- [Advanced Topics](#advanced-topics)

- [Jupyter Notebooks](#jupyter-notebooks)



## Setup and Introduction



- Customization of development environment

- Overview of different hardware/software and computational tools (Mac, Overleaf, etc.)

- Introduction to terminal commands, shell types, and text editors like Vim



## Data Management



- Usage of Overleaf for collaborative work

- Downloading and managing datasets



## General Commands and Environment Setup



- Basic terminal commands (exit, reset, etc.)

- Checking Python and Anaconda versions

- Introduction to Jupyter Notebooks



## Python Basics



- Basic Python programming concepts

- Simple projects and exercises, including a basic calculator



## Math, Numpy, Pandas, and Matplotlib



- Introduction to mathematical operations, data analysis, and data visualization



## Git and GitHub



- Project structuring and version control using Git



## Advanced Topics



- Advanced visualization techniques

- Special characters in Python and their usage



## Jupyter Notebooks



This repository contains Jupyter Notebooks corresponding to the Python portion of the course. These notebooks provide interactive exercises and examples to reinforce the concepts covered in the lectures. The notebooks are organized by day and topic, making it easy to follow along with the course progression.



### Notebooks Included



1. **Day 4 - Python Basics**

   - Introduction to Python syntax and basic projects



2. **Day 5 & 6 - Math, Numpy, Pandas, and Matplotlib**

   - Practical exercises on data analysis and visualization



3. **Day 8 - Advanced Topics**

   - Advanced exercises on visualization and special Python features



## How to Use



1. Clone the repository:

   ```sh

   git clone https://github.com/elcarrillo/computational_bootcamp_material.git

   ```

2. Navigate to the repository:

   ```sh

   cd computational_bootcamp_material

   ```

3. Open the Jupyter Notebooks:

   ```sh

   jupyter notebook

   ```

  NOTE: It is recommended to make use of a conda environment



## Contributing



Contributions to this repository are welcome. Please feel free to open issues or submit pull requests with any improvements or additional content.



## License



This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.