Aris Nivorlis
Aris Nivorlis is a researcher geophysicist and data steward at Deltares, where he uses data and tooling to answer complex questions about the subsurface.
He is passionate about promoting good practices in data management and scientific coding, helping teams build sustainable and reproducible workflows.
Outside of work, Aris is actively involved in the European Python community, contributing to the organization and support of conferences and community initiatives.
When he's not at his computer, you’ll likely find him dancing salsa.
Session
Your analysis works perfectly on your laptop. Three weeks later, it breaks on the server. Your colleague can't run your code nor reproduce your results. The client's environment throws mysterious errors. Sound familiar?
This hands-on workshop teaches you to build modern reproducible workflows using a holistic framework that addresses real challenges teams face when sharing code, collaborating on research, or deploying data pipelines.
You'll gain practical experience on:
* Modern tooling to manage Python environments and dependencies
* Version control your code and data
* Use configuration files to store your parameters
* Containerize your application for easy deployment
* Best practices for team collaboration
The workshop is ideal for data scientists, researchers, and Python developers with intermediate experience who are tired of "works on my machine" syndrome. You’ll gain hands-on experience with modern tools and practices that make Python workflows reproducible, maintainable, and easy to share, all while applying them to simply data science tasks.