Workshop on Reproducible Research
Open and Reproducible Science Using Python and GitHub
2:30 p.m. - 4:30 p.m., NIH Library Training Room, Building 10
Open and reproducible science requires researchers to be able to easily build, document, and share their analysis pipeline. In this workshop you’ll get a basic introduction to Python and GitHub, two of the most popular tools in the field used to accomplish these goals. Python is a programming language that can be used for data acquisition, wrangling, analysis, visualization and more. Once you have written your code in Python (or other programming languages), you can host your project on GitHub, which allows you to share code, edit code collaboratively, and track your changes with version control.
In this hands-on workshop, you’ll set up your GitHub account, write a simple Python program, and practice editing and collaborating with colleagues. PLEASE NOTE: You will need to bring your own laptop to the workshop. Instructions for installation of required software will be distributed in advance of the workshop, and the instructor will be available to assist with installation and configuration.
Registration for this workshop is now closed.
For questions, please contact Lisa Federer (NIH/OD) (email@example.com).
About the Instructors
Adam Thomas leads the Data Science and Sharing Team in the NIMH Intramural Research Program. He earned his D.Phil from the University of Oxford in Neuroscience and his researched is focused on structural brain plasticity measured with neuroimaging. Adam is also a regular instructor for Data Carpentry and Software Carpentry on campus and is a strong advocate of Open Science.
John Rodgers-Lee studied olfactory behavior using electrophysiology and calcium imaging in the Drosophila model organism for his graduate studies. He is part of the Data Science and Sharing Team (DSST) at NIMH. Along with teaching techniques for improved reproducibility in neuroscience, he also helps to upload data collected at NIMH to online repositories.