• 1

    Keynotes

    • Are We Ready for the Era of Analytics Heterogeneity? Maybe… but the Data Says No by Marinela Profi

    • Health AI: What's Possible Now and What's Hard by Suchi Saria, PhD

    • A Secure Collaborative Learning Platform by Raluca Ada Popa, PhD

    • Data for Good: Ensuring the Responsible Use of Data to Benefit Society by Jeannette M. Wing, PhD

    • Our Applied AI Future by Ben Taylor, PhD

    • Applying AI to Real World Use Cases by John Montgomery

    • Generalized Deep Reinforcement Learning for Solving Combinatorial Optimization Problems by Azalia Mirhoseini, PhD

    • Frontiers of Probabilistic Machine Learning by Zoubin Ghahramani, PhD

    • The Future of Computing is Distributed by Ion Stoica, PhD
  • 2

    Demo Talks

    • What if AI Could Craft the Next Generation of your AI? by Yonatan Geifman, PhD

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

    • Personalize.AI: Transforming Businesses Through Personalization by Gopi Vikranth and Dr. Prakash

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

    • Integrating Open Source Modeling with SAS Model Manager by Scott Lindauer, PhD and Diana Shaw

    • Improving Your Data Visualization Flow with Altair and Vega-Lite by Rachel House

    • An Overview of Algorithmia: How to Deploy, Manage, and Scale Your Machine Learning Model Portfolio by Kristopher Overholt

    • DataRobot Enterprise AI Platform: End-to-End Demonstration by Andy Lofgreen

    • Responsible AI with Azure Machine Learning by Mehrnoosh Sameki, PhD

    • Accelerate Time-to-Model by Simplifying the Complexity of Feature Engineering by Daniel B Gray and John Lynch

    • [Deep Learning] Fresh Data in Days Instead of Months by Anthony Sarkis

    • Supercharge your Training Data Quality with Samasource by Abha Laddha

    • Budgeting, Building & Scaling Data Labeling Operations by Soo Yang

    • Implementing an Automated X-Ray Images Data Pipelines, the Cloud-native Way! by Guillaume Moutier

    • DataOps: The Secret Advantage for ML and AI Success by Cody Rich

    • Automated Model Management with ML Works by Pavan Nanjundaiah

    • Next-Generation Big Data Pipelines with Prefect and Dask by Aaron Richter, PhD

    • How to Increase ML Server Utilization With MLOps Visualization Dashboards by Yochay Ettun

    • HPCC Systems – The Kit and Kaboodle for Big Data and Data Science by Bob Foreman and Hugo Watanuki

    • Jumpstart Your Data Science Career with The Data Incubator by Sierra King

    • Meet the New Hot Analytics Stack - Apache Kafka, Spark and Druid by Danny Leybzon

    • Centralizing Data Science Work and Infrastructure Access Across the Enterprise by Ross Sharp
  • 3

    Career Mentor Talks

    • Mental Models for Building Your Career in Data Science by Chirasmita Mallick

    • A Data Scientist from Academia to Industry: things you should know! by Wjdan Alharthi

    • The Data Engineering Path by Daniela Petruzalek

    • How Data Scientists Can Support Their Organization's DEI Efforts by Timi Dayo-Kayode

    • Am I Ready for a Data Science Job? by Aadil Hussaini

    • Coding Challenges: What Are hiring Companies Looking For? by Arwen Griffioen, PhD

    • Data Science Success Stories by Jeff Anderson
  • 4

    Applied AI

    • How to Stop Worrying and Start Tackling AI Bias by Jett Oristaglio

    • Some Failures and Lessons Learned Using AI in our AI Company by Dustin Burke and Borys Drozhak

    • The Rise of MLOps by Seph Mard

    • Realizing Value through DataRobot’s AI-Powered Apps by Ina Ko

    • Lessons Learned with Data & Storytelling by Danny Ma, Kate Strachnyi, Jen Underwood, Susan Walsh, Ben Taylor, PhD

    • Experimentation, Metrics and Analytics: An Ecosystem for Data Informed Decisions by Eric Weber

    • Fireside Chat with Jacqueline Ros Amable - AI in Climate Tech by Ryan Sevey and Jacqueline Amable

    • Components of AI Infrastructure & MLOps by Michael Balint

    • Building an Analytics COE: One Leader's Story by Edward M. Young

    • Solving Practical Computer Vision Problems in 10 Minutes by Anton Kasyanov and Ivan Pyzow

    • Hands-on Data Science for Software Developers -- A Live Coding Session with Data Robot Self-Service by David Gonzalez

    • A Tutorial on Robust Machine Learning Deployment by Tim Whittaker and Rajiv Shah, PhD

    • The AI Practitioner Series - Data Prep Walkthrough (A Reusable Framework!) by Sean Smith and Shyam Ayyar

  • 5

    Extras

    • ODSC Ignite: Women in Data Science

    • AI Investors Reverse Pitch

    • Learning from Failure - Incredible Stories from Successful Business Leaders