Jupyter Notebooks: Getting started with interactive and reproducible data analysis


To book, please visit: oxford.onlinesurveys.ac.uk/jupyter-notebooks-getting-started-with-interactive-and-re-2
We will cover how the use of an interactive coding environment, such as that provided by Jupyter Notebooks, can help with reproducibility and open research practices. The course will include setting up a Jupyter notebook, as well as overview of features and resources for further learning.
Topics to be covered – Why use tools such as an interactive notebook? – Reproducibility, environments and containers. – Jupyter: Installing and getting started. – Teaching yourself: Jupyter for exploring. – Sharing: showing your working. – The Jupyter ecosystem.
Learning Objectives – Steps that can help with reproducible data analysis. – Options for describing research computing environments. – Conda environment and install packages for using Jupyter notebooks. – Basic features of a Jupyter notebook. – Many routes to continue learning about Jupyter and Python
Prior knowledge required
Some programming experience would be useful. Code will be in Python, but lack of experience should not be a barrier for participation.
Intended Audience
Anyone who is exploring and analyzing data, with and interest in reproducibility and open working practices.
Type of Session
Short talk plus live-coding and a Q&A. Option to follow along with either pre-shared notebooks or with mybinder.org and any web browser.
Software Required
None necessary, although materials could be made available for those who have brought laptops with them with Miniconda (docs.conda.io/en/latest/miniconda.html), or the full Anaconda Python distribution installed.