Summary and Setup

This short course is teaching tools and practices for producing and sharing quality, sustainable and FAIR (Findable, Accessible, Interoperable and Reusable) research software to support open and reproducible research. The course can be delivered over 2 full or 4 half days.

Target Audience

  • Post-graduate students, early career researchers or junior Research Software Engineers (RSEs) who are starting their research or software projects, have foundational knowledge of Python, version control and using software tools from command line shell, and want to develop software to support their research using established best practices
  • Researchers or scientists who had foundational software training before but wish to refresh, reinforce or improve their skills and practices in the wider context of FAIR research and sharing and writing software for open and reproducible research

Check out a few example learner profiles, to see if this course is a right fit for you.

Prerequisites

Before joining this training, participants must have foundational knowledge of Python used to write scientific code, version control system Git and a command line (shell) tool to be able to understand code examples used in the course.

Attending a Software Carpentry or a similar course could help with these requirements and gaining necessary prerequisite skills.

Please also make sure you have all the required software installed before attending this course.

Learning Objectives

After attending this training, you will be able to:

  • List challenges typically faced by researchers developing software (and managing data) for modern computational, reproducible research, including those commensurate with the FAIR (Findable, Accessible, Interoperable, Reusable) principles
  • Build on top of your existing knowledge of Python, Git and command line tools to enhance your research software development workflow with some good open and reproducible research software practices around structuring, writing, documenting, testing, sharing and reusing code (including software licencing and citation)
  • Understand some ethical issues around research software development and usage and how our work impacts others

What we do not teach

This course assumes the prior knowledge of and does not focus on teaching:

  • Python code syntax or skills (even though Python is used in code examples)
  • the basic Git workflow
  • how to navigate file systems, manipulate files and invoke Python scripts and tools from a command line terminal/shell.

Setup

To go through the course material on your own or at a workshop, you will need the following software installed and working correctly on your system:

Please follow the installation instructions to install the above tools and set up for the course.