An open-source, interactive textbook for learning practical Python skills in health data science and machine learning. The material is available as a free online Jupyter Book:
👉 Read the Book

👥 Who This Is For

• Healthcare researchers and practitioners new to programming
• Data scientists looking to specialize in health applications
• Students in health data science, health informatics, biostatistics, or related fields
• Anyone interested in applying Python to real-world health problems
• NHS or healthcare data scientists

👨‍💻 About

Created and maintained by Thomas Monks and contributors.

✨ Features

• Interactive Jupyter Book: Step-by-step guides, hands-on code examples, and exercises
• Health Data Focus: Real health data scenarios and healthcare-specific best practices
• Open and Free: Fully open-source and accessible to everyone
• Multiple Access Options: Read online, run in the cloud, or install locally
• Reproducible Environment: All dependencies managed via Conda

📋 Prerequisites

• Basic familiarity with Python (helpful but not required)
• Interest in health data and healthcare applications
• Access to a computer with internet connection

🚀 Quick Start

1. Read Online

• Browse all book contents at: pythonhealthdatascience.com

2. Run Code in the Cloud

• Launch an interactive version via Binder with all dependencies pre-installed.

3. Local Installation

1. Clone this repository:

   git clone https://github.com/health-data-science-OR/coding-for-ml.git
   cd coding-for-ml

2. Install the virtual environment:

   conda env create -f binder/environment.yml
   conda activate hds_code

3. Launch JupyterLab:

   jupyter-lab

All required packages and dependencies are specified in binder/environment.yml.

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📚 Table of Contents

• Introduction and prerequisites
• Algorithms and computational modelling
• Statistical programming
• Managing data science projects

📝 Citation

If this book or its code helps your work, please cite the Zenodo record:

@software{monks_thomas_2023_8377497,
  author       = {Monks, Thomas},
  title        = {{Python for health data science: a hands-on 
                   introduction}},
  month        = sep,
  year         = 2023,
  note         = {{Please cite this software using the 
                   metadata from this file.}},
  publisher    = {Zenodo},
  version      = {v2.0.1},
  doi          = {10.5281/zenodo.8377497},
  url          = {https://doi.org/10.5281/zenodo.8377497}
}

🤝 Contributing

Contributions, suggestions, and feedback are welcomed! Please open an issue or fork and issue a pull request on the GitHub repository.

📄 License

Distributed under the MIT License. See LICENSE for more information.

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