January 11-12, 2018
9:00am - 4:30pm
Instructors: Emily Jane McTavish, Hilmar Lapp, Tracy Teal
Helpers: Martha Kandziora, Elizabeth Salmon, Jasper Toscani Field
Data Carpentry aims to help researchers work effectively and reproducibly with data by teaching them foundational research computing skills. This is a pilot Data Carpentry workshop with new curriculum on the Jupyter notebook.
In this workshop you will learn how to use the Jupyter notebook as a tool for good practices in reproducible research. Jupyter notebooks are increasingly widely adopted, and have been the main method of displaying detailed results in a number of high-profile scientific papers. As a tool promoting reproducible practices, Jupyter notebooks allow users to interleave text, code, and output into a single, interactive document that includes features facilitating research exploration, interactive learning, and sharing over the internet. Their dynamic nature is ideally suited to sharing all steps of the research workflow in a reproducible manner.
Participants will be encouraged to help one another and to apply what they have learned to their own research problems.
Who: The course is aimed at graduate students, postdocs, and other researchers who perform computational analysis or work. The material uses basic Python for teaching and illustrating the key concepts. Advanced knowledge of Python is not needed, but some familiarity with Python will aid in absorbing the material.
Where: COB1 263 (Classroom and Office Building 1).
When: January 11-12, 2018. Add to your Google Calendar.
Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by Data Carpentry's Code of Conduct.
Accessibility: We are committed to making this workshop accessible to everybody. The workshop organisers have checked that:
Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.
Contact: Please email for more information.
Draft schedule General overview of the workshop: https://reproducible-science-curriculum.github.io/workshop-RR-Jupyter/
| Introduction to Reproducible Research |
| Data and Project Organization |
| Data Exploration |
| Automation |
| Publication and Sharing |
We will use this collaborative document for chatting, taking notes, and sharing URLs and bits of code.
Please be sure to complete these surveys before and after the workshop.