alpha, n Workforce Development Program

Resources

Tools, guides, and materials for current program participants.

Getting Started

Google Group

The program communicates through a Google Group. Contact Amy Roberts (amy.roberts@ucdenver.edu) or James deBoer (Richard.J.deBoer.12@nd.edu) to be added. Once you're a member you'll receive program emails and can browse the full message history.

Program Data

Data for the program is distributed through the Google Group. Once you have been added to the group, follow the instructions there to access the data files.

Code Repository

The analysis code lives on GitHub. Request write access by contacting the program staff, then clone the repository to your local machine to get started.

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Software Installation

Terminal

A terminal gives you access to the command line. On Mac, Terminal is built in — no installation needed. On Windows, install Windows Terminal from the Microsoft Store.

Mac → Windows →

Git

Git is a version control system used to track changes in code and collaborate with others. Install it before using the command line or cloning the code repository.

Mac → Windows →

Spyder

Spyder is a Python development environment designed for scientific computing. It includes a code editor, variable explorer, and interactive console.

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Visual Studio Code

VS Code is a general-purpose code editor with strong Python support, extensions, and an integrated terminal. A good choice if you prefer a more flexible editor than Spyder.

Mac → Windows →

Tutorials

Software Carpentry: The Unix Shell

An introduction to navigating the file system, running commands, and writing simple scripts in the Linux/Mac terminal. Start here if the command line is new to you.

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Software Carpentry: Version Control with Git

A beginner-friendly guide to tracking changes with Git, working with branches, and collaborating on GitHub. Recommended before making your first commit to the analysis repository.

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Software Carpentry: Plotting and Programming in Python

An introduction to Python for people with little or no programming experience, using real scientific data. Covers data loading, functions, and visualization.

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Data Carpentry: Data Analysis in Python

A practical introduction to the pandas library for loading, cleaning, and analyzing tabular data in Python. Recommended once you are comfortable with basic Python.

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Science Background

Program Science Overview

A video introduction to the science behind the alpha, n program. Recommended viewing for all new students before diving into the analysis.

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Reference Papers

A curated collection of papers assembled by James deBoer covering the nuclear physics background relevant to the program. Hosted on Notre Dame Box.

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