(Serious) Time for Time Series
Marysia Winkels, James Hayward
Time Series

From inventory to website visitors, resource planning to financial data, time-series data is all around us. Knowing what comes next is key to success in this dynamically changing world. So join us and learn about time series analysis and seasonality modelling.

5 Years, 10 Sprints, A scikit-learn Open Source Journey
Reshama Shaikh
Community, Science, Statistics

In this keynote, I will share highlights, challenges and lessons learned. (

A Smooth Ride: Online Car Buying and Selling at
Ricardo Kawase, Marlene Hense
Best Practice, Career & Freelancing, Use Case

Buying or selling a car is a challenging task that requires a lot of difficult decision-making. We will reveal all the "under the hood" data products at that support users in making the right decisions.

Aspect-oriented Programming - Diving deep into Decorators
Mike Müller
Algorithms, Architecture, Python fundamentals

Functions that take functions and return new functions can be fun. Python's everything-is-an-object principle at work.

Beyond the basics: Contributor experience, diversity and culture in open source projects
Melissa Weber Mendonça
Community, Diversity & Inclusion, Governance

In this talk, we'll explore actions and assumptions about DEI and how they relate to volunteer work and open-source communities, how we can go beyond the basics when engaging new contributors, and improving a project's culture around inclusiveness and different axes of diversity.

Building an ORM from scratch
Jonathan Oberländer, Patrick Schemitz
Art, Databases

From an empty Python file to a fully-featured ORM in 45 minutes

But this is an OAuth, is it not?
Sara Jakša
APIs, Backend

OAuth simplified and secured third-party integrations for the end user. But for the developer of the integration, it can still present some friction. This talk talks about examples of real-life problems that were encountered by implementing multiple OAuth integrations.

Career Panel
Katharine Jarmul, Matteo Guzzo, Sieer Angar, Marielle Dado, Emily Gorcenski
Career & Freelancing

Are you thinking about a career change? In our career panel we will discuss different aspects with participants from different fields.

Challenge Accepted - How to Escape the Quicksand While Engineering a Computer Vision Application
Bettina Heinlein
Computer Vision

Leveraging problem-solving strategies for challenges in building Computer Vision applications and beyond, illustrated with a recent Computer Vision project.

Come as you are: Transitioning from Science to Data Science
Dr. Hannah Bohle
Career & Freelancing

Come as you are: Transitioning from Science to Data Science. How to find your first job in industry after leaving academia.

conda-forge: supporting the growth of the volunteer-driven, community-based packaging project
Wolf Vollprecht, Jannis Leidel, Jaime Rodríguez-Guerra
Community, Packaging, Python - PyPy, Cython, Anaconda

How does the conda-forge packaging community work, what is its relationship to conda and PyPI and how can everyone package software with it?

Creating 3D Maps using Python
Martin Christen
GIS / Geo-Analytics

Create 3DMaps anywhere on the planet using Python and OpenData

Data Science at Scale with Dask
Richard Pelgrim
APIs, Big Data, Cloud

A hands-on introduction to methods for scaling your data science and machine learning with Dask.

Do we really need Data Scientists?
Dr. Setareh Sadjadi
Career & Freelancing, Community

Is Data Science really cooling down? Do we need Data Scientists? What for?

Easy and flexible imaging with the Core Imaging Library
Vaggelis Papoutsellis, Dr. Jakob Sauer Jørgensen
Algorithms, Big Data, Math

Core Imaging Library is an open-source, object-oriented Python library for inverse problems in imaging developed by the UK academic network CCPi.

Efficient data labelling with weak supervision
Maria Mestre
Data Engineering, Data Visualization, Natural Language Processing

Data labelling should not be a waterfall task. Label your data significantly faster with weak supervision (

Fast native data structures: C/C++ from Python
Stefan Behnel
Big Data, Parallel Programming / Async, Python - PyPy, Cython, Anaconda

Need fast data access in Python? Use native data structures with Cython!

Forget ‘web 3.0’, let's talk about ‘web 0.0’. A brief history of the Internet, and the World Wide Web.
Dom Weldon
Art, Social Sciences, Theory

Forget ‘web 3.0’, let's talk about ‘web 0.0’. A brief history of the Internet, and the World Wide Web.

Grokking LIME: How can we explain why an image classifier "knows" what’s in a photo without looking inside the model?
Kilian Kluge
Computer Vision, Neural Networks / Deep Learning, Transparency / Interpretability

How can LIME explain machine-learning models without peeking inside? Let's find out!

How a simple streamlit dashboard will help to put your machine learning model in production
Daniël Willemsen, Welmoet Verbaan
Best Practice, Data Visualization, Predictive Modelling

Have you struggled getting your valuable machine learning model into the hands of users? A simple streamlit monitoring dashboard can help!

How to deal with toxic people
Gina Häußge
Best Practice, Community

As an open source maintainer, sooner or later you'll encounter ungrateful, entitled or outright toxic people who can be a real drain on your motivation and general mental health. Here are some coping strategies that work for me!

How to Find Your Way Through a Million Lines of Code
Jürgen Gmach
Best Practice

Scared of a new project? @jugmac00 will show you "How to Find Your Way Through a Million Lines of Code"

Impact of Cultivating a Diverse and Inclusive Workplace
Riya Bansal
Community, Diversity & Inclusion

Let’s face it. The positive impact of diversity and inclusion is no longer debatable.

Introduction to OPC-UA and industrial IoT: Liberate machines from the proprietary clutches of Big Hardware with the power of opcua-asyncio
Joey Faulkner
Backend, Hardware, Networks

Software around industrial hardware is still highly proprietary, which leads to bad UX and inefficient use of hardware. OPC-UA represents an earnest new start at the world of IIoT, and using opcua-asyncio, we can create this revolution in python.

Introduction to Uplift Modeling
Dr. Juan Orduz
Algorithms, Predictive Modelling, Statistics

In this talk we introduce uplift modelling, a method to estimate conditional average treatment effects (CATE) using machine learning estimators.

jsonargparse - Say goodbye to configuration hassles
Marianne Stecklina
Best Practice

A proper CLI would be nice, but you're way too lazy to write it? Join this talk to learn about the open-source library jsonargparse!

JupyterLite: Jupyter ❤️ WebAssembly ❤️ Python
Jeremy Tuloup
Jupyter, Reproducibility, Use Case

JupyterLite is a Jupyter distribution that runs entirely in the web browser, backed by in-browser language kernels such as the WebAssembly powered Pyodide kernel. JupyterLite enables data science and interactive computing with the PyData scientific stack, directly in the browser.

Machine Learning Testing Ecosystem of Python
Yunus Emrah Bulut
Computer Vision, Ethics (Privacy, Fairness,… ), Governance, Natural Language Processing, Neural Networks / Deep Learning, Security

Machine learning testing becomes an indispensable part of the MLOps and Python offers great ecosystem for this purpose.

Navigating the limitations of Python’s concurrency model in web services
Tarek Mehrez
APIs, Architecture, Parallel Programming / Async

Ever wondered when you should favor an async web framework? How do they compare to your good old python services when scaling is in question? Then this is the talk for you

Predictive Maintenance and Anomaly Detection for Wind Energy
Tobias Hoinka
Predictive Modelling, Statistics, Time Series

This talk will describe predictive modeling applications in wind turbine maintenance, the challenges of anomaly detection and ways to move to more automatic diagnoses by modeling past documented defects.

pytest - simple, rapid and fun testing with Python (3 hours)
Florian Bruhin
Best Practice, Development Methods

The #pytest tool presents a rapid and simple way to write tests for your Python code. This training gives an introduction with exercises to some distinguishing features.

Python for Everyone - PyLadies' Insights Panel Discussion
Jessica Greene (she/her)
Community, Diversity & Inclusion

Join this panel to learn more about how PyLadies volunteers and organizers make a difference, what they would like the wider python community to understand, so they could be more effective in their work, and what you could do tomorrow, to help advance this work.

Dr. Kristian Rother
Best Practice, Coding / Code-Review, Development Methods

Refactor a space travel game by introducing functions, classes and data structures

Secure ML: Automated Security Best Practices in Machine Learning
Alejandro Saucedo
Best Practice, Data Engineering, Security

As data science capabilities scale, the core concept of security becomes growingly critical - in this talk we provide an overview of challenges, solutions and best practices to introduce security into the ML lifecycle.

Seeing the needle AND the haystack: single-datapoint selection for billion-point datasets
Jean-Luc Stevens
Big Data, Data Visualization, Jupyter

Building simple custom interactive web dashboards that display millions or billions of samples while giving access to each individual sample.

Stupid Things I've Done With Python
Mark Smith
Best Practice, Coding / Code-Review, Python fundamentals

On every computer I've had for the past 20 years, I've created a folder called "stupid python tricks". It's where I put code that should never see the light of day. Code I'm going to teach you.

The Magic of Python Objects
Coen de Groot
Python fundamentals

Discover the Magic of Python Objects and the 125+ methods that keep them running

The Myth of Neutrality: How AI is widening social divides
Stefanie Stoppel
Ethics (Privacy, Fairness,… ), Neural Networks / Deep Learning

AI is not neutral and its creation often perpetuates harmful biases. My talk highlights how difficult it is to build "fair and responsible" AI, but also why it's worth to try & prevent these algorithms from cementing existing injustices.

Unclear Code Hurts
Dario Cannone
Best Practice, Coding / Code-Review

Code may work or not, but it will always tell a story. Computers will not complain about how you write it (except correct syntax), but human readers will. This talk is about writing clear code and caring for the human beings that will read it. Yourself included.

Your data, your insights: creating personal data projects to (re-)own the data you share
Paula Gonzalez Avalos
Data Visualization, Predictive Modelling

Your data, your insights: 3 examples to illustrate how we can apply common data science libraries together with data shared via mobile apps or collected manually to build little data visualization projects that provide unique, contextual and intmiate insights.