Keynotes, Conference Talks, Demo talks and Career Lab Sessions

  • 01

    ODSC Europe Keynotes

    • Data Excellence: Better Data for Better AI by Dr. Lora Aroyo

    • Data Science Change Is Inevitable, Growth Is Optional by Dr. Iain Brown

    • Machine Learning for Exoplanet Discovery by Dr. David Armstrong

  • 02

    Demo talks

    • First Aid Kit for Data Science: Keeping Machine Learning Alive by Véronique Van Vlasselaer, PhD

    • eXplainable Predictive Decisioning: Combine ML and Decision Management to Promote Trust on Automated Decision Making by Matteo Mortariand Daniele Zonca

    • Build and Deploy Custom AI Predictive Models by Yamini Rao

    • A Quick, Practical Overview of KNIME Analytics Platform by Paolo Tamagnin

    • Best Practices: Partnerships between ML/AI and Data Labeling Companies by Soo Yang

    • An Overview of Algorithmia: the Industry Leading Machine Learning Operations and Management Platform by Kristopher Overholt

    • Leverage Data Lineage to Maximize the Benefits of Big Data by Ernie Ostic

    • Is Infrastructure Holding Back Adoption of AI at Scale? by Nick Patience

    • Revision Control for Structured Data by Gavin Mendel-Gleason

    • Sports Analytics - Leveraging Open Source Technology to Improve Athlete Performance by Christopher Connelly

    • Annotating Data with AI-assisted Labelling by Eric Landau

    • VerticaPy Demo : Building a Prediction Churn Model Using Random Forest & Logistic Regression by Badr Ouali

    • Creating Efficiency and Trust with MLOps by Jan van der Vegt

    • Build Your Own Cloud Native Covid-19 Data Analytics with Kubernetes and OpenShift by Dr. Mo Haghighi

    • Learn How to Seamlessly Use Julia for Your Machine Learning Tasks by Dr. Matt Bauman

  • 03

    Career Lab Talks

    • Changing Career Paths: be a Data Scientist! by Bea Hernández

    • Demystifying Data Science Roles and Responsibilities by Eva-Marie Muller-Stuler, PhD

    • The Data Engineering Path by Daniela Petruzalek

    • Who is a Data Scientist? by Behrooz Afghahi

    • Navigating Data Science Interviews by Shrilata Murthy

  • 04

    Conference Talks

    • Can Your Model Survive the Crisis: Monitoring, Diagnosis and Mitigation by Jiahang Zhong, PhD

    • Practical, Rigorous Explainability in AI by Tsvi Lev

    • Practical Methods to Optimise Model Stability: A Case Study Using Customer-Lifetime Value at Farfetch by Davide Sarra and Kishan Manani, PhD

    • Sprinting Pandas by Ian Ozsvald

    • A Gentle Intro to Transformer Neural Networks by Jay Alammar

    • Integrating Small Data, Synthetic Data in AI and Data Strategy for Fashion Retail by Andrey Golub, PhD

    • Knowledge Graphs for the Greater Good by Bojan Božić, PhD

    • Training a Machine to See What’s Beautiful (esp. for Hotel Photos) by Dat Tran

    • Knowledge Graph Extraction for the Enterprise by Dr. Paul Buitelaar and Dr. John McCrae

    • Making Happy Modelers: Build and Maintain Your Data Warehouse with AWS Redshift and Airflow by Stephanie Kirmer

    • Tracking Coal and Solar Power with Machine Learning and Satellites by Laurence Watson

    • Deep Learning for Anomaly Detection by Nisha Muktewar

    • Ensuring Ethical Practice in AI by Sray Agarwal

    • Forecasting the Economy with Fifty Shades of Emotions by Sonja Tilly, CFA

    • Sustainable Retail Through Open Source, Scraping and NLP by Joanneke Meijer

    • Image Detection as a Service: How we Use APIs and Deep Learning to Support our Products by Laura Mitchell

    • Beyond OCR: Using Deep Learning to Understand Documents by Eitan Anzenberg, PhD

    • Snakes on a Plane: Interactive Data Exploration with PyFlink and Zeppelin Notebooks by Marta Paes

    • Building Personalized Scores for Customers: How to Combine Different Data Types and Learn in the Process by Svetlana Vinogradova, PhD

    • Dare to Start Simple by Dr. Katharina Glass

    • Have I Got (Financial) News for You by Alun Biffin, PhD

    • Multivariate (Flight) Anomalies Detection by Marta Markiewicz

    • CRESST: Complete Rare Event Specification Using Stochastic Treatment by Debanjana Banerjee

    • What Do I See in This Data? Visual Tools to Enhance Data Understanding by Max Novelli

    • Your Future, Today. Using NLP to Advance Your Career by Gabrielle Fournet, PhD

    • Machine Learning Operations: Latent Conditions and Active Failures by Flavio Clesio

    • Needles in a Haystack: Big Data and Bigger Promises? by Khurshid Ahmad, PhD

    • Which is the Tallest Building in Europe? — Representing and Reasoning About Knowledge by Ian Horrocks, PhD

    • Automated Insights in Finance Using Machine Learning & AI by Dr. Arun Verma

    • On the Automation of Data Science by Luc De Raedt, PhD

    • Leveraging Artificial Intelligence to Better Exploit Open Educational Resources by John Shawe-Taylor, PhD

    • VerticaPy: Demystifying Machine Learning Complexity with Python at Scale by Badr Ouali

    • Model Governance: A Checklist for Getting AI Safely to Production by David Talby, PhD

    • Provenance: a Fundamental Data Governance Tool ⎯ a Case Study for Data Science Pipelines and Their Explanations by Luc Moreau, PhD

    • Algorithmic Confounding in Recommendation Systems by Allison Chaney, PhD

    • From Longitudinal Patient Observational Data to Individualized Treatments Effects Using Causal Inference by Ioana Bica

    • Predicting Future Decisions with Deep learning for Financial Trading by Ning Wang, PhD and Yuting Fu

    • Natural Language Processing: Feature Engineering in the Context of Stock Investing by Frank Zhao

    • Building Fair and Explainable AI Pipelines by Margriet Groenendijk, PhD

    • Cloud Platforms for AI - Why You Should Care About DevOps, Containers and Kubernetes by Steven Huels

    • Democratizing Data for the Enterprise by Sherard Griffin

    • The Evolution of Data Labeling by Soo Yang

    • At Last, a Good Night’s Sleep! Operationalizing your Models the Correct Way by Thodoris Petropoulos

What to expect from on-demand all access pass for ODSC Europe Virtual?

  • Trainings & Workshops

    50+ training sessions over 4 days, ODSC Europe brings the breadth and depth of data science

  • Real World Applications

    Gain the skills and knowledge to use data science in your career and business, without breaking the bank.

  • Cutting Edge Subject Matter

    Find training sessions offered on a wide variety of data science topics, from machine learning to data visualization to MLOps.