Schedule
Time -> Sessions
More than 112 sessions await you.
Monday, April 11 Morning
09:00
10:20 - 10:50
11:20 - 14:20
A03-A04
Tutorial: pytest - simple, rapid and fun testing with Python (3 hours)
Florian Bruhin (Bruhin Software)
PyCon: Testing • Best Practice, Development Methods11:20 - 12:50
A05-A06
Tutorial: sktime - python toolbox for time series: advanced forecasting - probabilistic, global and hierarchical
Franz Kiraly
PyData: PyData & Scientific Libraries Stack • Algorithms, Predictive Modelling, Time Series11:25 - 12:10
Kuppelsaal
Talk: What I learned from monitoring more than 30 Machine Learning Use Cases
Lina Weichbrodt (DKB AG)
General: Production • Best Practice, Backend, DevOps11:25 - 12:10
B09
Talk: Fundamentals of relational databases
Katharina Rasch (freelance)
PyData: Data Handling • Databases11:25 - 12:10
B07-B08
Talk: The Myth of Neutrality: How AI is widening social divides
Stefanie Stoppel (inovex GmbH)
General: Ethics • Ethics (Privacy, Fairness,… ), Neural Networks / Deep Learning11:25 - 12:10
B05-B06
Talk: Processing Open Street Map Data with Python and PostgreSQL
Travis Hathaway
PyData: Data Handling • Data Engineering, Databases, GIS / Geo-Analytics11:25 - 12:10
A1
Talk: Rewriting your R analysis code in Python
Helena Schmidt
General: Python & PyData Friends • Best Practice, Development Methods, R12:20 - 12:50
Kuppelsaal
Talk: Building a Sign-to-Speech prototype with TensorFlow, Pytorch and DeepStack: How it happened & What I learned
Steven Kolawole
PyData: Computer Vision • Computer Vision, Neural Networks / Deep Learning12:20 - 13:05
B09
Talk: Building an ORM from scratch
Jonathan Oberländer (solute GmbH), Patrick Schemitz
PyCon: Libraries • Art, Databases12:20 - 13:05
B07-B08
Talk: You shall not share!
Gönül Aycı (Utrecht University)
PyData: Machine Learning & Stats • Ethics (Privacy, Fairness,… ), Natural Language Processing12:20 - 12:50
B05-B06
Talk: Creating 3D Maps using Python
Martin Christen (FHNW - University of Applied Sciences and Arts Northwestern Switzerland)
PyData: PyData & Scientific Libraries Stack • GIS / Geo-Analytics12:20 - 13:05
A1
Talk: Introduction to Uplift Modeling
Dr. Juan Orduz
PyData: Machine Learning & Stats • Algorithms, Predictive Modelling, Statistics12:30
12:30
12:40
12:40
12:40
12:40
12:40
Monday, April 11 Afternoon
13:40 - 13:50
13:45 - 14:30
Kuppelsaal
Keynote: Beyond the basics: Contributor experience, diversity and culture in open source projects
Melissa Weber Mendonça (Quansight)
Plenary • Community, Diversity & Inclusion, Governance14:30
14:30
14:30
14:30
14:30
14:45 - 17:45
A03-A04
Tutorial: pytest - simple, rapid and fun testing with Python (3 hours)
Florian Bruhin (Bruhin Software)
PyCon: Testing • Best Practice, Development Methods14:45 - 16:15
A05-A06
Tutorial: Inpsect and try to interpret your scikit-learn machine-learning models
Guillaume Lemaitre (Inria)
PyData: Machine Learning & Stats • Predictive Modelling, Statistics, Transparency / Interpretability15:00 - 16:00
Kuppelsaal
Panel: Career Panel
Katharine Jarmul, Matteo Guzzo, Sieer Angar (KÖNIGSWEG GmbH), Marielle Dado, Emily Gorcenski
General: Community, Diversity, Carreer, Life and everything else • Career & Freelancing15:00 - 15:30
B09
Talk: A Smooth Ride: Online Car Buying and Selling at mobile.de
Ricardo Kawase (mobile.de), Marlene Hense (mobile.de)
General: Production • Best Practice, Career & Freelancing, Use Case15:00 - 15:30
B07-B08
Talk: Python 3.10: Welcome to pattern matching!
Laysa Uchoa (Aiven)
PyCon: Python Language • Best Practice, Coding / Code-Review, Python fundamentals15:00 - 15:30
B05-B06
Talk: Introducing the Dask Active Memory Manager
Guido Imperiale (Coiled)
PyData: PyData & Scientific Libraries Stack • Algorithms, Architecture, Backend, Cloud, Data Engineering, Distributed Computing, Parallel Programming / Async15:00 - 15:30
A1
Talk: Impact of Cultivating a Diverse and Inclusive Workplace
Riya Bansal (Microsoft)
General: Community, Diversity, Carreer, Life and everything else • Community, Diversity & Inclusion15:40 - 16:10
B09
Talk: Seeing the needle AND the haystack: single-datapoint selection for billion-point datasets
Jean-Luc Stevens (Anaconda)
PyData: Visualization • Big Data, Data Visualization, Jupyter15:40 - 16:10
B07-B08
Talk: Trojan Source Malware - Can we trust open-source anymore?
Cheuk Ting Ho (TerminusDB)
PyCon: Python Language • Community, Governance, Python fundamentals, Security, Transparency / Interpretability15:40 - 16:10
B05-B06
Talk: Data Apis: Standardization of N-dimensional arrays and dataframes
Stephannie Jimenez Gacha (Quansight)
PyData: PyData & Scientific Libraries Stack • APIs15:40 - 16:40
A1
Talk: The secret sauce of data science management
Shir Meir Lador (Intuit)
PyData: Machine Learning & Stats • Best Practice, Big Data, Career & Freelancing, Corporate16:20
Tuesday, April 12 Morning
08:30
09:00 - 09:30
Kuppelsaal
Talk: Biases in Language Models
sonam (saama technologies)
General: Ethics • Diversity & Inclusion, Ethics (Privacy, Fairness,… ), Natural Language Processing09:00 - 09:30
B09
Talk: Speeding up Python with Zig
Adam Serafini (Delivery Hero)
PyCon: Libraries • Packaging, Performance09:00 - 09:30
B07-B08
Talk: Secure ML: Automated Security Best Practices in Machine Learning
Alejandro Saucedo (The Institute for Ethical AI & Machine Learning)
PyData: Machine Learning & Stats • Best Practice, Data Engineering, Security09:00 - 09:30
B05-B06
Talk: How a simple streamlit dashboard will help to put your machine learning model in production
Daniël Willemsen (GoDataDriven), Welmoet Verbaan (Bol.com)
PyData: Visualization • Best Practice, Data Visualization, Predictive Modelling09:00 - 09:30
A1
Talk: deepdoctection - An open source package for document intelligence
Janis Meyer (self employed)
PyData: Natural Language Processing • Computer Vision, Natural Language Processing09:00 - 10:30
A03-A04
Tutorial: Faster Workflow with Testdriven Development
Torsten Zielke (moguru GmbH)
PyCon: Testing • Best Practice, Backend, Coding / Code-Review09:00 - 10:30
A05-A06
Tutorial: Data Science at Scale with Dask
Richard Pelgrim (Coiled)
PyData: PyData & Scientific Libraries Stack • APIs, Big Data, Cloud09:40 - 10:05
Kuppelsaal
Talk: How to deal with toxic people
Gina Häußge (OctoPrint)
General: Community, Diversity, Carreer, Life and everything else • Best Practice, Community09:40 - 10:25
B09
Talk: Unsupervised shallow learning for fraud detection on marketplaces
Andreu Mora (Adyen)
PyData: Machine Learning & Stats • Algorithms, Best Practice, Predictive Modelling09:40 - 10:25
B07-B08
Talk: conda-forge: supporting the growth of the volunteer-driven, community-based packaging project
Wolf Vollprecht (QuantStack), Jannis Leidel (Anaconda, conda-forge, PSF, PyPA), Jaime Rodríguez-Guerra (Quansight)
General: Python & PyData Friends • Community, Packaging, Python - PyPy, Cython, Anaconda09:40 - 10:25
B05-B06
Talk: Flexible ML Experiment Tracking System for Python Coders with DVC and Streamlit
Antoine Toubhans (Sicara)
PyData: PyData & Scientific Libraries Stack • Best Practice, Computer Vision, Data Engineering, Data Visualization, Development Methods, Reproducibility09:40 - 09:55
A1
Talk: `python-m5p` - M5 Prime regression trees in python, compliant with scikit-learn
Sylvain Marié (Schneider Electric)
PyData: Machine Learning & Stats • Algorithms, Predictive Modelling, Science10:20
10:20
10:20
10:20
10:20
10:30
10:30
10:45 - 12:15
A03-A04
Tutorial: ML Communication 101: How to talk about Machine Learning with anyone
Julia Ostheimer (kineo.ai / DSSG Berlin e.V.)
General: Community, Diversity, Carreer, Life and everything else • Best Practice, Business & Start-Ups, Career & Freelancing, Corporate, Diversity & Inclusion, Ethics (Privacy, Fairness,… ), Transparency / Interpretability, Use Case10:45 - 12:15
A05-A06
Tutorial: We know what your app did last summer. Do you? Observing Python applications using Prometheus.
Jessica Greene (she/her) (Ecosia), Vanessa Aguilar (Ecosia GmbH)
PyCon: DevOps • Data Visualization, DevOps, Performance10:50 - 11:20
Kuppelsaal
Talk: 5 Things You Want to Know About AI Adoption in the Enterprise
Alexander CS Hendorf (Königsweg GmbH)
General: Production • Architecture, Best Practice, Business & Start-Ups, Corporate, Diversity & Inclusion10:50 - 11:20
B09
Talk: Using a database in a data science project - Lessons learned in production
Jacopo Farina (Flixbus)
PyData: Data Handling • Data Engineering, Databases10:50 - 11:20
B07-B08
Talk: Unclear Code Hurts
Dario Cannone
General: Python & PyData Friends • Best Practice, Coding / Code-Review10:50 - 11:20
B05-B06
Talk: Predictive Maintenance and Anomaly Detection for Wind Energy
Tobias Hoinka (scieneers GmbH)
PyData: Machine Learning & Stats • Predictive Modelling, Statistics, Time Series10:50 - 11:20
A1
Talk: Your data, your insights: creating personal data projects to (re-)own the data you share
Paula Gonzalez Avalos (SPICED Academy)
PyData: Visualization • Data Visualization, Predictive Modelling11:30 - 12:00
Kuppelsaal
Talk: Do we really need Data Scientists?
Dr. Setareh Sadjadi (Diconium GmbH)
General: Community, Diversity, Carreer, Life and everything else • Career & Freelancing, Community11:30 - 12:15
B09
Talk: 5 Things we've learned building large APIs with FastAPI
Maarten Huijsmans (InvestSuite)
PyCon: Web • APIs, Best Practice11:30 - 12:00
B07-B08
Talk: A data scientist's guide to code reviews
Alexandra Wörner (scieneers)
General: Python & PyData Friends • Coding / Code-Review11:30 - 12:15
B05-B06
Talk: Making Machine Learning Applications Fast and Simple with ONNX
Jan-Benedikt Jagusch (QuantCo), Christian Bourjau (QuantCo)
General: Production • Data Engineering, DevOps, Packaging11:30 - 12:00
A1
Talk: Sankey Plots with Python
Daniel Ringler (DB Systel)
PyData: Visualization • Data Visualization, Jupyter, Python fundamentals12:00
12:00
12:00
12:00
12:00
12:15
12:15
13:00 - 14:30
A03-A04
Tutorial: Aspect-oriented Programming - Diving deep into Decorators
Mike Müller (Python Academy)
PyCon: Programming & Software Engineering • Algorithms, Architecture, Python fundamentals13:00 - 14:30
A05-A06
Tutorial: Reproducible machine learning and science with python
Prabhant Singh (TU Eindhoven/OpenML)
PyData: PyData & Scientific Libraries Stack • Best Practice, Community, Science13:10 - 13:40
Kuppelsaal
Talk: Detecting drift: how to evaluate and explore data drift in machine learning systems
Emeli Dral (Evidently AI)
PyData: Machine Learning & Stats • Best Practice, Data Visualization, Statistics13:10 - 13:40
B09
Talk: Forget ‘web 3.0’, let's talk about ‘web 0.0’. A brief history of the Internet, and the World Wide Web.
Dom Weldon (Decision Lab)
General: Community, Diversity, Carreer, Life and everything else • Art, Social Sciences, Theory13:10 - 13:40
B07-B08
Talk: What are data unit tests and why we need them
Theodore Meynard (GetYourGuide)
PyData: Data Handling • Best Practice, Data Engineering13:10 - 13:40
B05-B06
Talk: Overcoming 5 Hurdles to Using Jupyter Notebooks for Data Science, by the JetBrains Datalore Team
Alena Guzharina (JetBrains)
PyData: Jupyter • Data Visualization, Jupyter, Reproducibility13:10 - 13:40
A1
Talk: Battle of Pipelines - who will win python orchestration in 2022?
Jannis Grönberg (Kineo.ai)
PyCon: DevOps • Architecture, Data Engineering, DevOpsTuesday, April 12 Afternoon
13:50 - 14:20
Kuppelsaal
Talk: Efficient data labelling with weak supervision
Maria Mestre (DataQA)
PyData: Natural Language Processing • Data Engineering, Data Visualization, Natural Language Processing13:50 - 14:20
13:50 - 14:35
B07-B08
Talk: Machine Learning Testing Ecosystem of Python
Yunus Emrah Bulut (Karlsruhe Institute of Technology (KIT))
PyData: Machine Learning & Stats • Computer Vision, Ethics (Privacy, Fairness,… ), Governance, Natural Language Processing, Neural Networks / Deep Learning, Security13:50 - 14:25
B05-B06
Talk: JupyterLite: Jupyter ❤️ WebAssembly ❤️ Python
Jeremy Tuloup (QuantStack)
PyData: Jupyter • Jupyter, Reproducibility, Use Case13:50 - 14:20
A1
Talk: The state of DevOps for Python projects
Tobias Heintz (alcemy GmbH)
PyCon: DevOps • Data Engineering, Development Methods, DevOps14:20
14:20
14:20
14:20
14:20
14:30
14:30
14:45 - 16:15
A03-A04
Tutorial: Introduction to MLOps with MLflow
Tobias Sterbak
General: Production • Best Practice, Predictive Modelling, Reproducibility14:45 - 16:15
A05-A06
Tutorial: Easily build interactive plots and apps with hvPlot
Philipp Rudiger (Anaconda Inc.), Maxime Liquet (Anaconda)
PyData: Visualization • Data Visualization, Jupyter, Science14:50 - 15:50
Kuppelsaal
Panel: Python for Everyone - PyLadies' Insights Panel Discussion
Jessica Greene (she/her) (Ecosia)
General: Community, Diversity, Carreer, Life and everything else • Community, Diversity & Inclusion14:50 - 15:20
B09
Talk: Stupid Things I've Done With Python
Mark Smith (MongoDB)
PyCon: Programming & Software Engineering • Best Practice, Coding / Code-Review, Python fundamentals14:50 - 15:20
B07-B08
Talk: Web based live visualisation of sensor data
Jannis Lübbe (ROSEN)
PyCon: Web • APIs, Data Visualization, Use Case14:50 - 15:20
B05-B06
Talk: Honey, I shrunk the target variable! Common pitfalls when transforming the target variable and how to exploit transformations.
Florian Wilhelm (inovex GmbH)
PyData: Machine Learning & Stats • Math, Predictive Modelling, Statistics14:50 - 15:15
A1
Talk: Challenge Accepted - How to Escape the Quicksand While Engineering a Computer Vision Application
Bettina Heinlein (HITS (Heidelberg Institute for Theoretical Studies))
PyData: Computer Vision • Computer Vision15:30 - 16:00
B09
Talk: Slack bots 101: An introduction into slack bot-based workflow automation
Jordi Smit (GoDataDriven | Part of Xebia)
General: Python & PyData Friends • APIs, DevOps, Use Case15:30 - 16:00
B07-B08
Talk: Make the most of Django
Paolo Melchiorre (20tab)
PyCon: Django • Best Practice, Community, Django15:30 - 16:00
B05-B06
Talk: My forecast is better than yours! What does that even mean?
Illia Babounikau (BlueYonder)
PyData: Machine Learning & Stats • Statistics, Time Series15:30 - 16:00
A1
Talk: Grokking LIME: How can we explain why an image classifier "knows" what’s in a photo without looking inside the model?
Kilian Kluge (XAI-Studio & Inlinity AI)
PyData: Computer Vision • Computer Vision, Neural Networks / Deep Learning, Transparency / Interpretability15:50
15:50
15:50
15:50
15:50
16:15
16:15
16:20 - 16:30
16:30 - 17:15
Kuppelsaal
Keynote: 5 Years, 10 Sprints, A scikit-learn Open Source Journey
Reshama Shaikh (Data Umbrella)
Plenary • Community, Science, Statistics17:15
18:30
19:00 - 00:00
Wednesday, April 13 Morning
08:30
09:00 - 09:10
09:10 - 09:55
Kuppelsaal
Keynote: Python 3.11 in the Web Browser - A Journey
Christian Heimes (Red Hat)
PyCon: Programming & Software Engineering • Python - CPython new features10:00 - 11:30
A03-A04
Tutorial: (Serious) Time for Time Series
Marysia Winkels (GoDataDriven), James Hayward
PyData: PyData & Scientific Libraries Stack • Time Series10:00 - 11:30
A05-A06
Tutorial: Refactoring
Dr. Kristian Rother (Freelance)
PyCon: Programming & Software Engineering • Best Practice, Coding / Code-Review, Development Methods10:05 - 10:35
Kuppelsaal
Talk: It is all about files and HTTP
Efe Öge (Hipo)
PyCon: Web • APIs, Architecture, Backend, Cloud, DevOps, Django10:05 - 10:50
B09
Talk: Easy and flexible imaging with the Core Imaging Library
Vaggelis Papoutsellis (Science and Technology Facilities Council, UK Research and Innovation), Dr. Jakob Sauer Jørgensen (Technical University of Denmark)
PyData: PyData & Scientific Libraries Stack • Algorithms, Big Data, Math10:05 - 10:50
B07-B08
Talk: How to build a Python-based Research Cloud Platform from scratch
Andre Fröhlich (Quoniam Asset Management GmbH)
General: Production • Architecture, Business & Start-Ups, Use Case10:05 - 10:50
B05-B06
Talk: Fast native data structures: C/C++ from Python
Stefan Behnel
PyCon: Programming & Software Engineering • Big Data, Parallel Programming / Async, Python - PyPy, Cython, Anaconda10:05 - 10:50
A1
Talk: Introduction to OPC-UA and industrial IoT: Liberate machines from the proprietary clutches of Big Hardware with the power of opcua-asyncio
Joey Faulkner (Green Fusion)
PyCon: Libraries • Backend, Hardware, Networks11:00 - 11:30
Kuppelsaal
Talk: "Easy Python": lies, damned lies, and metaclasses
Grigory Petrov (Evrone), Maxim Danilov
PyCon: Python Language • Best Practice, Coding / Code-Review, Development Methods11:00 - 11:30
B09
Talk: Optimize your network inference time with OpenVINO
Adrian Boguszewski (Intel)
PyData: Deep Learning • Jupyter, Neural Networks / Deep Learning, Performance11:00 - 11:45
B07-B08
Talk: Squirrel - Efficient Data Loading for Large-Scale Deep Learning
Dr. Thomas Wollmann (Merantix Momentum)
PyData: Data Handling • Distributed Computing, Neural Networks / Deep Learning, Parallel Programming / Async11:00 - 11:30
B05-B06
Talk: Demystifying Python's Internals: Diving into CPython by implementing a pipe operator
Sebastiaan Zeeff (Ordina Pythoneers)
PyCon: Python Language • Python - CPython new features, Python fundamentals11:00 - 11:30
A1
Talk: Do I need to be Dr. Frankenstein to create real-ish synthetic data?
Gatha (Amity University, Noida)
General: Ethics • Data Engineering, Ethics (Privacy, Fairness,… ), Governance11:30
11:30
11:30
11:30
11:30
11:30
11:30
11:45 - 13:15
A03-A04
Tutorial: PPML: Machine Learning on Data you cannot see
Valerio Maggio (University of Bristol)
PyData: Data Handling • Neural Networks / Deep Learning, Security11:45 - 13:15
A05-A06
Tutorial: An Introduction to Inter Process Communication and Synchronization using Python
Tanmoy Bandyopadhyay (Capgemini)
PyCon: Libraries • Algorithms, Coding / Code-Review, Parallel Programming / Async12:00 - 12:30
Kuppelsaal
Talk: Securing Django Applications
Gajendra Deshpande (KLS Gogte Institute of Technology)
PyCon: Django • Best Practice, Django, Security12:00 - 12:30
B09
Talk: Forget Mono vs. Multi-Repo - Building Centralized Git Workflows with Python
David Melamed (Jit)
PyCon: DevOps • Cloud, Coding / Code-Review, DevOps, Security12:00 - 12:30
B07-B08
Talk: Come as you are: Transitioning from Science to Data Science
Dr. Hannah Bohle (indblik.io)
General: Community, Diversity, Carreer, Life and everything else • Career & Freelancing12:00 - 12:30
B05-B06
Talk: On Blocks, Copies and Views: updating pandas' internals
Joris Van den Bossche (Voltron Data)
PyData: PyData & Scientific Libraries Stack • APIs, Data Structures12:00 - 12:30
A1
Talk: Can you Read This? (Or: how I Improved Text Readability on the Web for the Visually Impaired)
Asya Frumkin (Evinced)
PyData: Computer Vision • Algorithms, Computer Vision, Neural Networks / Deep Learning12:40 - 13:10
12:40 - 13:10
B09
Talk: Quitting pip: How we use git submodules to manage internal dependencies that require fast iteration
Philipp Stephan (mediaire)
PyCon: DevOps • Best Practice, Development Methods, DevOps, Packaging12:40 - 13:10
B07-B08
Talk: XAI meets Natural Language Processing
Larissa Haas (sovanta AG)
PyData: Natural Language Processing • Data Visualization, Ethics (Privacy, Fairness,… ), Transparency / Interpretability12:40
12:40 - 13:25
13:10
13:10
13:10
13:10
13:10
13:15
13:15
Wednesday, April 13 Afternoon
14:00 - 14:30
Kuppelsaal
Talk: How to Find Your Way Through a Million Lines of Code
Jürgen Gmach (Canonical)
PyCon: Programming & Software Engineering • Best Practice14:00 - 14:30
B09
Talk: Financial Portfolio Management with Deep Reinforcement Learning
T-Berger (Datamics)
PyData: Deep Learning • Neural Networks / Deep Learning, Simulation, Time Series14:00 - 14:30
B07-B08
Talk: 5 Steps to Speed Up Your Data-Analysis on a Single Core
Jonathan Striebel (scalable minds GmbH)
PyData: PyData & Scientific Libraries Stack • Data Engineering, Performance14:00
14:00 - 14:30
A1
Talk: Performing Content: Can NLP and Deep Learning algorithms predict reader preferences?
Sebastian Cattes (INWT Statistics)
PyData: Natural Language Processing • Natural Language Processing, Neural Networks / Deep Learning, Statistics14:00 - 15:30
A03-A04
Tutorial: Making MLOps uncool again
David (iterative.ai)
PyData: Machine Learning & Stats • Best Practice, Development Methods, Reproducibility14:00 - 15:30
A05-A06
Tutorial: Practical graph neural networks in Python with TensorFlow and Spektral
Aleksander Molak (Tensorcell)
PyData: Deep Learning • Graphs, Neural Networks / Deep Learning14:40 - 15:10
Kuppelsaal
Talk: There Are Python 2 Relics in Your Code
Miroslav Šedivý (Trayport Austria GmbH)
PyCon: Python Language • Coding / Code-Review, Python - CPython new features, Python fundamentals14:40 - 15:10
B09
Talk: How to Trust Your Deep Learning Code
Tilman Krokotsch (IAV GmbH)
PyData: Deep Learning • Best Practice, Neural Networks / Deep Learning14:40 - 15:25
B07-B08
Talk: Navigating the limitations of Python’s concurrency model in web services
Tarek Mehrez (Klarna)
PyCon: Web • APIs, Architecture, Parallel Programming / Async14:40 - 15:10
B05-B06
Talk: jsonargparse - Say goodbye to configuration hassles
Marianne Stecklina (omni:us)
PyCon: Libraries • Best Practice14:40 - 15:25
A1
Talk: Transformer based clustering: Identifying product clusters for E-commerce
Sebastian Wanner (idealo.de), Christopher Lennan (idealo Internet GmbH)
PyData: Natural Language Processing • Natural Language Processing, Neural Networks / Deep Learning, Use Case15:10
15:10
15:10
15:10
15:10
16:00 - 16:30
16:30
17:00