Data Science is Software: Developer #lifehacks for the Jupyter Data Scientist
Data Science is Software: Developer #lifehacks for the Jupyter Data Scientist


While we don’t always think about it this way, the job or the data scientist is to build software. Often data scientists use only the most rudimentary of software engineering tools. It’s time we leverage the tools and best practices of software engineering that have been built over the last 25 years. This workshop covers the less sexy, but critical parts of building software: project structure, testing, debugging (the world beyond print statements), logging, source control, linting, and collaboration. The workshop will cover these topics in a hands on way looking at Python code through the IDE, Jupyter notebooks, and at the command line. The workshop will be useful to anyone who does data science in Python and wants to build more robust and reliable code.



Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Consent to display content from - Youtube
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google