Accelerate Python with Julia
Stephan Sahm

You want to accelerate your Python code, but going C is too tedious? Julia is a fresh alternative which flows like Python and runs like C. Join this tutorial to learn how to use Julia to easily speed up Python.

Cloud Infrastructure From Python Code: How Far Could We Go?
Etzik Bega, Asher Sterkin

Why Infrastructure as Code is not enough and what needs to be done to make Python trully cloud-native programming language?

How to increase diversity in open source communities
Maren Westermann

Learn about strategies for increasing diversity in #opensource projects presented by @MarenWestermann

Panel Session

Panel Session: Content to be announced. Wait just a little longer ;-)

Pyladies Workshop

Pyladies Workshop xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Python Meets UX: Enhancing User Experience with Code
Neeraj Pandey, Aashka Dhebar

"Join us for a talk on the intersection of Python and UX design. Learn how Python is being used to automate tasks, gather user feedback, and create personalized user experiences. Explore the future of Python in UX and discover the challenges and opportunities it presents.

The CPU in your browser: WebAssembly demystified
Antonio Cuni

WebAssembly is essentially a virtual and efficient CPU embedded in your browser. Let's see what it is!

Thou Shall Judge But With Fairness: Methods to Ensure an Unbiased Model
Nandana Sreeraj

Biased models can impact each of us. While it may feel abstract, AI fairness can be achieved through many methods and metrics. More so, mitigation reports can initiate you to responsible AI. Check out my talk & demo at PyData Berlin.

What could possibly go wrong? - An incomplete guide on how to prevent, detect & mitigate biases in data products
Lea Petters

Data Ethics: What could possibly go wrong? - An incomplete guide on how to prevent, detect & mitigate biases in data products

Workshop on Privilege and Ethics in Data
Tereza Iofciu, Paula Gonzalez Avalos

Data-driven Products are built by humans. Humans are intrinsically biased. This bias goes into the products, which amplifies the original bias. In this tutorial, you will learn how to identify your biases and reflect on the consequences of unchecked biases in Data Products.