This course introduces more advanced tools to increase the reproducibility of data analyses; building upon the Intro to Reproducibility course. GitHub, Docker, Code Review, and GitHub actions are discussed.
This course on AI for software development explores the use of AI large language models (ChatGPT, Bard, etc) and their potential benefits and challenges. Hands-on activities show the ways in which AI can speed up software development tasks and free up time for more creative and strategic work, maximizing benefits/efficiency while limiting harm.
This course covers the basics of creating documentation and tutorials to maximize the usability of informatics tools. It is meant for individuals developing tools for informatics.
This course covers how to use containers for scientific software development. Scientific software benefits from the concepts of continuous integration (CI) and continuous deployment (CD). Containers play a critical role in CI/CD by providing a consistent, portable, and isolated environment for building, testing, and deploying software.
This course walks through why's and the how's for using automation to boost scientific software development process.
A capstone course for the ITN Reproducibility Series with hands-on activities
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