Announcing a pilot workshop on "Reproducible Research Using the Jupyter Notebook" on Jan. 11 and 12.
The objective of this workshop is to learn about and work with the Jupyter notebook as a tool promoting best practices for 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. The notebooks' dynamic nature is ideally suited to sharing all steps of the research workflow in a reproducible manner.
Although this workshop will use Python as the programming language, Jupyter notebooks can be used with more than 40 common programming languages, and the notebook document format is programming language-agnostic.
The event is organized jointly by Data Carpentry and the Jupyter Notebook project.
The workshop 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.
Please sign up at:
You will need to commit to attending both days of the workshop.
Please contact Professor Emily Jane McTavish at email@example.com if you have questions.