Conferences / PyData
PyData Amsterdam 2025
Sep 24–26, 2025 · de Kromhouthal (conference, 25-26 Sep); TNW City (tutorial day, 24 Sep), Amsterdam, Netherlands
- Conference
- PyData Data science & ML
- Dates
- Sep 24, 2025 – Sep 26, 2025
- Venue
- de Kromhouthal (conference, 25-26 Sep); TNW City (tutorial day, 24 Sep)
- Place
- Amsterdam, Netherlands
- Format
- In person
- Status
- Past
- Attendance
- —
- Website
- amsterdam.pydata.org
- Recorded
- 23 sponsors · 83 speaker appearances
- Notes
- 10th-anniversary edition. Sponsor logos shown under "Powered by" without tier labels (identified from links/logo files; the logo linked to odido.nl but showing Spare Cores is recorded as Spare Cores, plus Odido separately). Prices from the pretix shop (final listed prices; earlier early-bird tiers not captured). Speakers: full list from the pretalx schedule export; affiliations parsed from pretalx speaker bios (null where the bio states no clear current employer/institution).
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| Student Conference Pass (2 days) | €187 | — | pretix.eu | |
| Tutorial Pass (stand-alone, 24 Sep) | €200 | — | pretix.eu | |
| Day Pass (Thursday or Friday) | €325 | — | pretix.eu | |
| Individual Conference Pass (2 days) | €395 | — | pretix.eu | |
| Corporate Conference Pass (5+ bulk, each) | €500 | — | pretix.eu | |
| Corporate Conference Pass (2 days) | €550 | — | pretix.eu |
Sponsors 23
Community 2
- DevITjobs · Community Partners
- Marvelous MLOps · Community Partners
Speakers and talks 83
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Demetrios Brinkmann | MLOps Community | Keynote | The agentification of software (has a UX problem) | Video |
| Dr. Maria Börner | Westernacher Solutions | Keynote | Ethics is Not a Feature: Rethinking AI from the Ground Up | — |
| Hannes Mühleisen | DuckDB Labs | Keynote | Minus Three Tier: Data Architecture Turned Upside Down | — |
| Judith Dijk | European Defence Agency | Keynote | Image processing, artificial intelligence, and autonomous systems | — |
| Aarti Jha | Red Hat | Tutorial | Next-Level Retrieval in RAG: Techniques and Tools for Enhanced Performance | — |
| Adam Hill | ComplyAdvantage | Tutorial | Bridging the Gap: Building Robust, Tool-Integrated LLM Applications with the Model Context Protocol | — |
| Agustin Iniguez | Rabobank | Talk | Continuous monitoring of model drift in the financial sector | — |
| Antonino Ingargiola | Agile Lab | Talk | Large-Scale Video Intelligence | Video |
| Antonio Castelli | Booking.com | Talk | Scaling Trust: A practical guide on evaluating LLMs and Agents | Video |
| Arda Kaygan | — | Talk | Techie vs Comic: The sequel | Video |
| Başak Eskili | Booking.com | Talk | Diversity Isn’t a Buzzword, It’s a Business Case | — |
| Bauke Brenninkmeijer | — | Talk | Context is King: Evaluating Long Context vs. RAG for Data Grounding | Video |
| Benjamin Bossan | Hugging Face | Talk | Designing tests for ML libraries – lessons from the wild | Video |
| Chris Laffra | — | Talk | Microlog: Explain Your Python Applications with Logs, Graphs, and AI | — |
| Dana Arsovska | Ahold Delhaize | Tutorial | Event-Driven AI Agent Workflows with Dapr | — |
| Danica Fine | — | Talk | Quiet on Set: Building an On-Air Sign with Open Source Technologies | Video |
| Denis Gaitan | Rabobank | Talk | Continuous monitoring of model drift in the financial sector | — |
| Dick Abma | — | Talk | Potato breeding using image analysis in a production setting | — |
| Dima Baranetskyi | — | Talk | Kafka Internals I Wish I Knew Sooner: The Non-Boring Truths | Video |
| Evertjan Peer | KickstartAI | Talk | Detection of Unattended Objects in Public Spaces using AI | — |
| Fabio Lipreri | — | Talk | Model Context Protocol: Principles and Practice | Video |
| Florenz Hollebrandse | ING | Talk | Flip the Plan: Fast-Track Your AI/ML Model Integration with a Back-to-Front Implementation Strategy | — |
| Fokko Driesprong | Databricks | Talk | Open source sprints - PyIceberg & PyMC | — |
| Gabriele Orlandi | xtream | Talk | Model Context Protocol: Principles and Practice | Video |
| George Chouliaras | — | Talk | Scaling Trust: A practical guide on evaluating LLMs and Agents | Video |
| Gerben Dekker | — | Talk | The Gentle Monorepo: Ship Faster and Collaborate Better | Video |
| Gergely Daroczi | — | Talk | Resource Monitoring and Optimization with Metaflow | Video |
| Inge van den Ende | — | Talk | Kickstart Your Probabilistic Forecasting with Level Set and Quantile Regression Forests | Video |
| Irene Donato | Agile Lab | Talk | Large-Scale Video Intelligence | Video |
| Iryna Kondrashchenko | DataForce Solutions GmbH | Talk | Is Prompt Engineering Dead? How Auto-Optimization is Changing the Game | Video |
| Isabelle Donatz-Fest | Green Land | Talk | Help! There Are Humans in My Data! | Video |
| Itzel Belderbos | Adyen | Talk | No labels? No problem! - Hunting Fraudsters with Minimal Labels and Maximum ML | Video |
| Iva Gornishka | City of Amsterdam | Talk | Evaluating the alignment of LLMs to Dutch societal values | Video |
| Jaap Stefels | Adyen | Talk | No labels? No problem! - Hunting Fraudsters with Minimal Labels and Maximum ML | Video |
| Javier de la Rúa Martínez | Hopsworks | Talk | Composable Pipelines for ML: Automating Feature Engineering with Hopsworks’ Brewer | — |
| Jeroen Janssens | Posit | Talk | Actionable Techniques for Finding Performance Regressions | — |
| Joanna Pasiarska | — | Talk | What Works: Practical Lessons in Applying Privacy-Enhancing Technologies (PET) in Data Science | — |
| Judith Redi | Creative Fabrica | Talk | Leading through the GenAI hype cycle: the good, the bad, and the ugly | — |
| Konstantinos Tsoumas | Mars | Talk | Uncertainty Unleashed: Wrapping Your Predictions in Honesty with Conformal Prediction | Video |
| Laurens Samson | City of Amsterdam | Talk | Evaluating the alignment of LLMs to Dutch societal values | Video |
| Lenar Sharipov | JetBrains | Tutorial | Building AI Agents With Observability Tooling in PyCharm | — |
| Lisette van der Zande | Topigs Norsvin | Talk | From pixel to predictions: A journey through our CT image pipeline in pig breeding using POSIT | — |
| Maarten de Ruiter | Xomnia | Talk | GenAI governance in practice: patterns, pitfalls & strategies across tools and industries | Video |
| Mahima Arora | Red Hat | Tutorial | Next-Level Retrieval in RAG: Techniques and Tools for Enhanced Performance | — |
| Manolis Manousogiannis | — | Talk | Data that Keeps Our Energy in Balance - From churn prediction with deep learning to real-time trading systems | — |
| Manu Joseph | Hopsworks | Talk | Real-Time Context Engineering for LLMs | Video |
| Manuel Spierenburg | — | Talk | Should Captain America Still Host Your Data? A Call for Open, EU-Based Data Platforms. | Video |
| Marc Duiker | Diagrid | Tutorial | Event-Driven AI Agent Workflows with Dapr | — |
| Maria Bader | Mollie | Talk | How to Keep Your LLM Chatbots Real: A Metrics Survival Guide | Video |
| Marten koopmans | Sopra Steria | Talk | Measure twice, deploy once: Evaluation of retrieval systems | — |
| Martin O'Hanlon | — | Tutorial | Understand your data with Knowledge Graphs | — |
| Marysia Winkels | Cohere | Talk | Help! There Are Humans in My Data! | Video |
| Miguel Leite | Adyen | Talk | Declarative Feature Engineering: Bridging Spark and Flink with a Unified DSL | Video |
| Mingxuan Zhao | IBM | Tutorial | Meet Docling: The “Pandas” for document AI | — |
| Muhammad Chenariyan Nakhaee | Exact | Talk | Searching for My Next Chart | Video |
| Nazlı Alagöz | Booking.com | Talk | Causal Inference Framework for incrementality : A Case Study at Booking to estimate incremental CLV due to App installs | Video |
| Netesh | — | Talk | Causal Inference Framework for incrementality : A Case Study at Booking to estimate incremental CLV due to App installs | Video |
| Niels Neerhoff | ING | Talk | Streamlining data pipeline development with Ordeq | — |
| Ninghang Hu | Tencent | Talk | Leading through the GenAI hype cycle: the good, the bad, and the ugly | — |
| Oleh Kostromin | — | Talk | Is Prompt Engineering Dead? How Auto-Optimization is Changing the Game | Video |
| Omar Hommos | Adyen | Talk | Leading through the GenAI hype cycle: the good, the bad, and the ugly | — |
| Oscar Ligthart | Vinted | Talk | Orchestrating success: How Vinted standardizes large-scale, decentralized data pipelines | Video |
| Pablo Estevez | — | Talk | Data that Keeps Our Energy in Balance - From churn prediction with deep learning to real-time trading systems | — |
| Panos Alexopoulos | Triply | Tutorial | Grounding LLMs on Solid Knowledge: Assessing and Improving Knowledge Graph Quality in GraphRAG Applications | — |
| Panos Vagenas | IBM | Tutorial | Meet Docling: The “Pandas” for document AI | — |
| Paul verhaar | — | Talk | Measure twice, deploy once: Evaluation of retrieval systems | — |
| Raphael Mitsch | — | Talk | Sieves: Plug-and-Play NLP Pipelines With Zero-Shot Models | Video |
| Rik Nuijten | Solynta | Talk | Potato breeding using image analysis in a production setting | — |
| Rob Zinkov | PyMC Labs | Talk | Open source sprints - PyIceberg & PyMC | — |
| Rodrigo Loredo | Vinted | Talk | Orchestrating success: How Vinted standardizes large-scale, decentralized data pipelines | Video |
| Sayak Paul | Hugging Face | Talk | Designing tests for ML libraries – lessons from the wild | Video |
| Shimanto Rahman | Ghent University | Talk | Optimize the Right Thing: Cost-Sensitive Classification in Practice | Video |
| Shourya Sharma | — | Tutorial | Bridging the Gap: Building Robust, Tool-Integrated LLM Applications with the Model Context Protocol | — |
| Simon Brugman | ING | Talk | Streamlining data pipeline development with Ordeq | — |
| Sven Arends | Picnic | Talk | Counting Groceries with Computer Vision: How Picnic Tracks Inventory Automatically | Video |
| Thijs Nieuwdorp | Xomnia | Talk | Actionable Techniques for Finding Performance Regressions | — |
| Tomek Roszczynialski | — | Tutorial | Listen: A Practical Introduction to Data Sonification | — |
| Vincent Warmerdam | — | Talk | Untitled13.ipynb | Video |
| Vitalie Spinu | Adyen | Talk | Optimal Observability: Partitioning Data into Time-Series for Enhanced Anomaly Detection and Improved Monitoring Coverage | Video |
| Vitalii Zhebrakovskyi | Adyen | Talk | Declarative Feature Engineering: Bridging Spark and Flink with a Unified DSL | Video |
| Wesley Boelrijk | KLM Royal Dutch Airlines | Talk | Formula 1 goes Bayesian: Time Series Decomposition with PyMC | — |
| Yaroslav Sokolov | JetBrains | Tutorial | Building AI Agents With Observability Tooling in PyCharm | — |
| Yuliya Sapega | — | Talk | What Works: Practical Lessons in Applying Privacy-Enhancing Technologies (PET) in Data Science | — |