Goal: To catalyze cancer informatics research through training opportunities. Go to itcrtraining.org for more information.
This course walks through why’s and the how’s for using automation to boost scientific software development process. It’s meant for folks who already have a basic familiarity with GitHub but would like to automate more of their software dev work.
This course walks through why’s and the how’s for using containers (e.g. Docker) to boost reproducibility of scientific analysis.
This course is designed for leaders and decision makers to have the high level overview of AI: it’s ethical implications, technical aspects to consider and more.
A course to cover the basics of creating documentation and tutorials to maximize the usability of informatics tools.
Equip learners with reproducibility skills they can apply to their existing analyses scripts and projects. This course opts for an “ease into it” approach; teaching “better practices”.
To equip learners with a deeper knowledge of the capabilities of reproducibility tools and how they can apply to their existing analyses scripts and projects.
To equip learners with the basic understanding and resources to handle their genomic data. The course is intended for students in the biomedical sciences and researchers who have been given data and don’t know what to do with it or would like an overview of the different genomic data types that are out there.
Looking for collaborators who’d like to write about their data type specialty See here for more info.
Goal: DataTrail aims to equip individuals with the tools they need to enter the booming field of data science.
Goal: To equip pediatric researchers with bioinformatics skills to fuel their research. See the Childhood Cancer Data Lab’s website for more information.