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Thank you to all our 7,400 Virtual Conference Attendees.  

A sincere thanks to our attendees, speakers, and partners for making our ODSC East Virtual Conference a resounding success.  Some useful links. 

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Training Sessions
Workshops
Speakers
Hours of Content

Data Science Virtual Conference & Expo

Accelerate your data science knowledge, training, and network.  All in one event.

ODSC East 2020 is one of the largest applied data science conferences in the world. Our speakers include core contributors to many open source libraries and languages. Attend ODSC East 2020 and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field.

Focus Areas

  • Deep Learning

  • Machine Learning

  • Predictive Analytics

  • AI for Engineers

  • Natural Language Processing

  • Data Visualization

  • Data Wrangling

  • AI Research

  • Data Science at Scale

  • Data Science for Good

  • Data Science Management

  • Data Science Workflows

  • AI Business Summit

Topics

  • Recommendation Systems

  • Transfer Learning

  • Machine Vision

  • Autonomous Machines

  • Conversational AI

  • Data Science Research

  • Artificial Intelligence

  • Speech Recognition

  • Unsupervised Learning

  • Image Classification

  • Self-driving Vehicles

  • Machine Translation

  • 200+ Speakers over 4 days

Tools

  • Python, Jupyter Notebooks

  • R programming, Julia, Scala, Stan

  • Apache Spark, MLlib, Streaming

  • Tensorflow, MXNet, Caffe, CNTK

  • Scikit-learn, Theano, Shogun, Pylearn2

  • Azure ML, Amazon ML,H20.ai, Cloud ML

  • Neo4J, D3.js, R-Shiny

  • Hadoop, Apache Storm, Apache Flink, Kafka, Druid

  • See schedule for many more..

 

East 2020 Keynotes

 

AllODSC KeynotesAi X KeynotesTrack Keynotes
Corporate Vice President, Program Management, AI PlatformMicrosoft

John Montgomery

John leads Program Management for Microsoft Azure AI and is responsible for designing products and services that data scientists and ML experts around the world love and use. He leads a team of program managers, researchers, and designers responsible for products and services including Azure Machine Learning, Azure Cognitive Services, ML.NET, and ONNX Runtime. Prior to this role, John has led the Program Management team for Microsoft’s Developer Division, including Visual Studio, Visual Studio Code, and Azure Notebooks.

He has also held positions as director of marketing for Visual Studio, as well as a program manager for Microsoft’s participation in several standards organizations, including ISO, IETF, and ECMA.

Prior to joining Microsoft in 1998, John worked as a writer and editor for several computer and technology publications, including BYTE Magazine, PC/Computing, and Corporate Computing, as well as being the Chief Information Officer for Imagine Publishing.

AI ResearcherGoogle Research and Machine Intelligence Group

Margaret Mitchell, PhD

Margaret is a Senior Research Scientist in Google’s Research & Machine Intelligence group, working on artificial intelligence.

Her research generally involves vision-language and grounded language generation, focusing on how to evolve artificial intelligence towards positive goals. This includes research on helping computers to communicate based on what they can process, as well as projects to create assistive and clinical technology from the state of the art in AI.

Her work combines computer vision, natural language processing, social media, many statistical methods, and insights from cognitive science.

Professor, National Center Chair, Founding DirectorWarren Center for Network and Data Sciences, UPenn

Michael Kearns, PhD

Michael Kearns is a professor in the Computer and Information Science department at the University of Pennsylvania, where he holds the National Center Chair and has joint appointments in the Wharton School.He is founder of Penn’s Networked and Social Systems Engineering (NETS) program, and director of Penn’s Warren Center for Network and Data Sciences. Michael is also the co-author of the book The Ethical Algorithm that talks about the science of designing algorithms that embed social values like privacy and fairness. His research interests include topics in machine learning, algorithmic game theory, social networks, and computational finance. He has worked and consulted extensively in the technology and finance industries. He is a fellow of the American Academy of Arts and Sciences, the Association for Computing Machinery, and the Association for the Advancement of Artificial Intelligence.

Michael has worked extensively in quantitative and algorithmic trading on Wall Street (including at Lehman Brothers, Bank of America, and SAC Capital; see further details below). He often serve as an advisor to technology companies and venture capital firms. He is also involved in the seed-stage fund Founder Collective and occasionally invest in early-stage technology startups. Michael is also a member of the Scientific Advisory Board of the Alan Turing Institute, and of the Market Surveillance Advisory Group of FINRA.

A.M. Turing Award Laureate, Professor, Co-founderMIT CSAIL, Tamr

Mike Stonebraker, PhD

Dr. Stonebraker has been a pioneer of database research and technology for more than forty years. He was the main architect of the INGRES relational DBMS, and the object-relational DBMS, POSTGRES. These prototypes were developed at the University of California at Berkeley where Stonebraker was a Professor of Computer Science for twenty five years. More recently at M.I.T., he was a co-architect of the Aurora/Borealis stream processing engine, the C-Store column-oriented DBMS, the H-Store transaction processing engine, the SciDB array DBMS, and the Data Tamer data curation system.
Presently he serves as Chief Technology Officer of Paradigm4 and Tamr, Inc.

Chief Science OfficerHugging Face 🤗

Thomas Wolf, PhD

Thomas leads the Science Team at Huggingface Inc., a Brooklyn-based startup working on Natural Language Generation and Natural Language Understanding.

After graduating from Ecole Polytechnique (Paris, France), he worked on laser-plasma interactions at the BELLA Center of the Lawrence Berkeley National Laboratory (Berkeley, CA). Got accepted for a PhD at MIT (Cambridge, MA) but ended up doing his PhD in Statistical/Quantum physics at Sorbonne University and ESPCI (Paris, France), working on superconducting materials for the French DARPA (DGA) and Thales.

Thomas is interested in Natural Language Processing, Deep Learning, and Computational Linguistics. Much of his research is about Natural Language Generation (mostly) and Natural Language Understanding (as a tool for better generation).

An Introduction to Transfer Learning in NLP and HuggingFace Tools(Workshop)

Professor, Co-Founder & Chief TechnologistStanford, Databricks

Matei Zaharia, PhD

Matei Zaharia is an Assistant Professor of Computer Science at Stanford University and Chief Technologist at Databricks. He started the Apache Spark project during his PhD at UC Berkeley in 2009 and has worked broadly in datacenter systems, co-starting the Apache Mesos project and contributing as a committer on Apache Hadoop. Today, Matei tech-leads the MLflow development effort at Databricks. Matei’s research work was recognized through the 2014 ACM Doctoral Dissertation Award for the best PhD dissertation in computer science, an NSF CAREER Award and several best paper awards.

Simplifying Data Science with Delta Lake and MLflow(Track Keynote)

Professor, Founding Editor-in-ChiefHarvard University, Harvard Data Science Review

Xiao-Li Meng, PhD

Xiao-Li Meng, the Whipple V. N. Jones Professor of Statistics, and the Founding Editor-in-Chief of Harvard Data Science Review, is well known for his depth and breadth in research, his innovation and passion in pedagogy, his vision and effectiveness in administration, as well as for his engaging and entertaining style as a speaker and writer. Meng was named the best statistician under the age of 40 by COPSS (Committee of Presidents of Statistical Societies) in 2001, and he is the recipient of numerous awards and honors for his more than 150 publications in at least a dozen theoretical and methodological areas, as well as in areas of pedagogy and professional development. He has delivered more than 400 research presentations and public speeches on these topics, and he is the author of “The XL-Files,” a thought-provoking and entertaining column in the IMS (Institute of Mathematical Statistics) Bulletin. His interests range from the theoretical foundations of statistical inferences (e.g., the interplay among Bayesian, Fiducial, and frequentist perspectives; frameworks for multi-source, multi-phase and multi- resolution inferences) to statistical methods and computation (e.g., posterior predictive p-value; EM algorithm; Markov chain Monte Carlo; bridge and path sampling) to applications in natural, social, and medical sciences and engineering (e.g., complex statistical modeling in astronomy and astrophysics, assessing disparity in mental health services, and quantifying statistical information in genetic studies). Meng received his BS in mathematics from Fudan University in 1982 and his PhD in statistics from Harvard in 1990. He was on the faculty of the University of Chicago from 1991 to 2001 before returning to Harvard, where he served as the Chair of the Department of Statistics (2004-2012) and the Dean of Graduate School of Arts and Sciences (2012-2017).

COVID-19: Unprecedented Challenges and Opportunities for Data Science (and Scientists) — Voices, Visions, and Ventures form Harvard Data Science Review(Keynote)

Founder & Executive DirectorDataKind

Jake Porway, PhD

A pioneer of the Data for Good movement, Jake Porway is an expert in the field of data and technology. As Founder and Executive Director of DataKind, a global nonprofit dedicated to using data science and AI in the service of humanity, he’s worked alongside the nonprofit community to drive social change with the power of data science since 2011. Jake’s career spans more than a decade in the data science sector as a statistician and computer scientist. He’s worked as a data scientist for The New York Times R&D Lab and was a research scientist studying machine learning and probabilistic modeling tasks with NASA, the Office of Naval Research, and other government agencies. A PopTech Social Innovation Fellow and a National Geographic Emerging Explorer, Jake was also noted as one of LinkedIn’s Next Wave Top Professionals 35 & Under, and his efforts have led to DataKind being named one of Fast Company’s Top 10 Most Innovative Nonprofits. Jake holds a B.S. in Computer Science from Columbia University and an M.S. and Ph.D. in Statistics from UCLA.


 

More keynotes announced soon

East 2020 Speakers & Instructors

100+ speakers and 120 sessions already confirmed!

Professor, Co-Founder & Chief TechnologistStanford, Databricks

Matei Zaharia, PhD

Matei Zaharia is an Assistant Professor of Computer Science at Stanford University and Chief Technologist at Databricks. He started the Apache Spark project during his PhD at UC Berkeley in 2009 and has worked broadly in datacenter systems, co-starting the Apache Mesos project and contributing as a committer on Apache Hadoop. Today, Matei tech-leads the MLflow development effort at Databricks. Matei’s research work was recognized through the 2014 ACM Doctoral Dissertation Award for the best PhD dissertation in computer science, an NSF CAREER Award and several best paper awards.

Simplifying Data Science with Delta Lake and MLflow(Track Keynote)

Head of AI EngineeringBloomberg

Dr. Anju Kambadur

Dr. Prabhanjan (Anju) Kambadur heads the AI Engineering group at Bloomberg. Anju leads a group of 100+ researchers and engineers who build solutions for Bloomberg clients in the areas of machine learning, natural language processing (NLP) and natural language understanding, information extraction, knowledge graphs, question answering, and table understanding. Previously, Anju was a research staff member in the Business Analytics and Mathematical Sciences Department at IBM Research’s Thomas J. Watson Research Center, where he worked on problems in machine learning, such as matrix sketching, genome-wide association studies, temporal causal modeling, and high-performance computing. He received his PhD from Indiana University. Anju has published peer-reviewed articles in the fields of high-performance computing, machine learning, and natural language processing.

AI Research at Bloomberg(Talk)

Research FellowHarvard University

Zona Kostic, PhD

Zona Kostic is a research, teaching, and innovation fellow at Harvard University. Her professional interests are at the intersection of data visualization, machine learning, and digital realities, with current research activities being specifically focused on semantic visual similarity and smart web-based interfaces. Previously, Zona was part of the Harvard Visual Computing Group developing immersive visual analytics systems that support the overlay of digital information over physical objects. She published six books, and a number of research works at scientific journals and conferences. Zona is also a co-founder of ArchSpike, a small venture that integrates data science and visualization with market modeling, allowing users to design buildings that better respond to future market demands.

Smart Technologies in Enhancing Browsing Experiences(Talk)

Assistant ProfessorMIT CSAIL

Jacob Andreas, PhD

Jacob Andreas is an assistant professor at MIT and a senior researcher at Microsoft Semantic Machines. His research focuses on language learning as a window into reasoning, planning and perception, and on more general machine learning problems involving compositionality and modularity. Jacob earned his Ph.D. from UC Berkeley, his M.Phil. from Cambridge (where he studied as a Churchill scholar) and his B.S. from Columbia. He has been the recipient of an NSF graduate fellowship, a Facebook fellowship, and paper awards at NAACL and ICML.

Opening the Pod Bay Doors: Building Intelligent Agents That Can Interpret, Generate and Learn from Natural Language(Tutorial)

learn data storytelling
Lead Data Storytelling TrainerStoryIQ

Diedre Downing

Diedre is a Lead Data Storytelling Trainer at StoryIQ where she helps organizations improve their communication with and about data. An accidental math teacher, Diedre learned the power of demystifying numbers in New York City classrooms and the power of influencing decision-makers with data during her time running WeTeachNYC.org for the NYC Department of Education. Diedre is an Adjunct Lecturer at Hunter College in New York and has spoken at NCTM, iNACOL, and Learning Forward about adult learning methodology and best practices in professional learning.

The Art (and Importance) of Data Storytelling(Talk)

ML Researcher, Adjunct ProfessorMicrosoft Research New England, Stanford University

Lester Mackey, PhD

Lester Mackey is a machine learning researcher at Microsoft Research, where he develops new tools, models, and theory for large-scale learning tasks driven by applications from healthcare, climate, recommender systems, and the social good. Lester moved to Microsoft from Stanford University, where he was an assistant professor of Statistics and (by courtesy) of Computer Science. He earned his PhD in Computer Science and MA in Statistics from UC Berkeley and his BSE in Computer Science from Princeton University. He co-organized the second-place team in the $1M Netflix Prize competition for collaborative filtering, won the $50K Prize4Life ALS disease progression prediction challenge, won prizes for temperature and precipitation forecasting in the yearlong real-time $800K Subseasonal Climate Forecast Rodeo, and received a best student paper award at the International Conference on Machine Learning.

Improving Subseasonal Forecasting in the Western U.S. with Machine Learning(Track Keynote)

Director of Data ScienceShopRunner

Ali Vanderveld, PhD

Ali Vanderveld is the Director of Data Science at ShopRunner, where her team leverages data from a network of over 100 retailers to build products for their 6 million members. Prior to ShopRunner, she was a staff data scientist at Civis Analytics, a consulting and software startup that helps companies, nonprofits, and political organizations better utilize their data. She has also worked at Groupon and as a technical mentor for the Data Science for Social Good Fellowship. Ali has a PhD in theoretical astrophysics from Cornell University and got her to start working as an academic researcher at Caltech, the NASA Jet Propulsion Laboratory, and the University of Chicago, working on the development teams for several space telescope missions, including ESA’s Euclid.

Using Computer Vision and NLP Together for Fashion Classification(Talk)

Research Professor of Financial Machine Learning | AI Asset ManagementNYU | Fidelity Investments

Igor Halperin, PhD

Quant/researcher with extensive experience in building cutting-edge statistical and predictive models and advanced machine learning algorithms to solve practical problems in finance and consumer analytics, especially within credit, portfolio risk modeling, capital forecast models, and optimal control models.

Reinforcement learning and inverse reinforcement learning in finance(Talk)

Deep Learning and Software GPU expert Nir Shavit
CEO, ProfessorNeural Magic, MIT

Nir Shavit, PhD

Nir Shavit is the CEO of Neural Magic, a machine learning startup that is currently in stealth mode and is a professor in the Department of Electrical Engineering and Computer Science at MIT. Shavit is a co-author of the book The Art of Multiprocessor Programming, is a recipient of the 2004 Gödel Prize in theoretical computer science and of the 2012 Dijkstra Prize in Distributed Computing, and is an ACM fellow. His recent interests include systems issues in machine learning and techniques for understanding how neural tissue computes by extracting connectivity maps of neural tissue, a field called connectomics.

The Software GPU: Making Inference Scale in the Real World(Talk)

Head of Data Science and AnalyticsBadoo (now MagicLab, which owns several apps)

Leonardo De Marchi

Leonardo De Marchi holds a Master in Artificial intelligence and has worked as a Data Scientist in the sports world, with clients such as the New York Knicks and Manchester United, and with large social networks, like Justgiving.

He now works as Head of Data Scientist and Analytics in Badoo, the largest dating site with over 420 million users. He is also the lead instructor at ideai.io, a company specialized in Reinforcement Learning, Deep Learning, and Machine Learning training.

Modern and Old Reinforcement Learning(Training)

Assistant ProfessorUniversity of Massachusetts Boston

Shan Jiang, PhD

Shan Jiang is an assistant professor at the College of Management at the University of Massachusetts Boston. He received a BS in management information systems from Tsinghua University, China, and the PhD degree in management information systems from the University of Arizona. His research interests include business intelligence, social media analytics, computational linguistics, and social network analysis. His research works have appeared in journals including IEEE Transaction on Knowledge and Data Engineering, ACM Transaction on Management Information Systems, Journal of the Association for Information Science and Technology, and Decision Support Systems.

Web Crawling for Research Data(Talk)

Head of Medical image Processing LabTel-Aviv University

Hayit Greenspan, PhD

Prof. Greenspan heads the Medical Image Processing and Analysis Lab at the Biomedical Engineering Dept. in the Faculty of Engineering, Tel-Aviv University. Prof. Greenspan has been conducting research in image processing and computer vision for the past 20 years, with a special focus on deep learning, image modeling and analysis, resolution augmentation, and content-based image retrieval. Prof. Greenspan received the B.S. and M.S. degrees in Electrical Engineering from the Technion- Israel Institute of Technology, in 1986 and 1989, respectively, and the Ph.D. degree in Electrical Engineering from CALTECH – California Institute of Technology, in 1994. She was a Postdoc with the Computer Science Division at U.C. Berkeley from 1995 to 1997. In 1997 she joined Tel-Aviv University.

From 2008 until 2011, Prof. Greenspan was a visiting Professor at Stanford University, Department of Radiology, Faculty of Medicine. She was also a visiting researcher at IBM Research in the Multi-modal Mining for Healthcare group, in Almaden CA. She is now also affiliated with the Computer Science Institute (ICSI) at Berkeley, CA.

Prof. Greenspan has 51 journal publications in top-ranking journals, and more than 100 conference publications. She is the inventor of several patents. She is an Associate Editor of the top ranking journal in Medical imaging (IEEE-TMI) and is an active member of several international professional societies.

Professor, DirectorStanford University | Stanford Center for Biomedical Informatics Research

Mark Musen, PhD

Dr. Musen is Professor of Biomedical Informatics and of Biomedical Data Science at Stanford University, where he is Director of the Stanford Center for Biomedical Informatics Research. Dr. Musen conducts research related to open science, intelligent systems, computational ontologies, and biomedical decision support. His group developed Protégé, the world’s most widely used technology for building and managing terminologies and ontologies. He served as principal investigator of the National Center for Biomedical Ontology, one of the original National Centers for Biomedical Computing created by the U.S. National Institutes of Heath (NIH). He directs the Center for Expanded Data Annotation and Retrieval (CEDAR), founded under the NIH Big Data to Knowledge Initiative. CEDAR develops semantic technology to ease the authoring and management of biomedical experimental metadata.

CEDAR: Information technology to enhance open science in the fight against COVID-19(Talk)

Over 150 speakers and 100+ sessions announced. Check Here. More coming soon

ODSC is the best community data science event on the planet. There are other events that cover special topics, or industries, etc., but ODSC is comprehensive and totally community-focused: it's the conference to engage, to build, to develop, and to learn from the whole data science community.

Kirk Borne - Principal Data Scientist and Executive Advisor at Booz Allen Hamilton @ ODSC East 2019

8 Focus Areas. 4 Days. One Data Science Conference

The largest applied data science conference is now 4 days, including mini-bootcamp days, 2 full training days, and 2 talks/workshops days. You get even more talks, trainings, and workshops spread over 8 focus areas. Accelerate your data science knowledge, training, and network all in one event.

ODSC in 60 Seconds

Conference Focus Areas

Hands-On Training & Workshops

See our Hands-on Training Sessions

Virtual Conference & On Demand Registration

Missed the Virtual Conference?  For a limited time only, on-demand passes are available until May 8th


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ODSC East will return to the Boston Hynes Convention center in May 20201

  

Upcoming 2020 Events

 

ODSC Europe Virtual Conference
more info
ODSC West, San Francisco
more info

.

How It Works

  • Virtual conference experience includes networking lounge area, speaker auditorium, expo halls, and prizes

  • Access multiple livestream tracks on Tuesday, Wednesday, Thursday, or Friday

  • Switch between sessions or tracks as your interests dictate

  • Multiple focus areas including deep learning, machine learning, NLP, research frontiers, AI X for business, and more

  • Sessions you missed can be viewed on demand at your leisure

  • Engage virtually with fellow attendees, speakers, and Expo partners

  • Participate in Q&A sessions with your speaker over live chat

  • Directly download slides and other session materials

  • (Training only) Access training and workshops prerequisites, notebooks, and other materials prior to training session starting

  • (Training only) Access hands-on training and workshops with instructor-led code labs and notebooks.

* Reservation is valid up to 5 minutes before the sessions starts.  
** Networking Events and receptions are open to all Bootcamp, Silver, Gold, Platinum, VIP, and Business Pass holders. However, the Tuesday Speaker reception is granted to VIP, andBusiness pass holders only.
** Recording are distributed by pass holders days and pass access. 

Registration Resources

Virtual Conference pass guide

Quick Pass Guide

Livestream 2-Day Pass | Access multiple tracks on April 16th & 17th that include 6 keynotes and all breakout sessions, as well as multiple remote speaker tracks. On demand recordings are not included.

Livestream &  On Demand Recordings Pass |  Get access to everything included in the Livestream 2-Day pass plus on demand recordings of all sessions from Thursday and Friday. On Demand recording will be accessible immediately with continued access for over 12 months. This does not include Tuesday and Wednesday workshop or training livestream or on demand sessions. 

Livestream Trainings, Talks, and Workshop & On Demand Recordings Pass |  3 Day pass (Wed-Fri) Get access to everything included in the Livestream 2-Day + On Demand pass + access all of Wednesday’s workshops and training sessions. You also get immediate On Demand access to all recorded sessions including talks, keynotes, AIX business, training, workshops etc. 

Livestream Trainings, Talks, and Workshop & On Demand Recordings Pass |  4 Day pass (Tue-Fri)

Incudes all access and On Demand included in the 3-day pass PLUS all Tuesday traning sessions livestream tracks and On Demand Recordings  

 

Pay by invoice/purchase order

You are able to buy your ticket via Invoice/Purchase Order (PO).

Please submit your request to receive a Purchase Order HERE.

Free Track passes to Combat COVID-19

Free ODSC Global Virtual Conference passes are available to the following groups

Free Track Passes and are not geographically restricted.

  • If you have recently become unemployed due to the COVID-19, 
  • If you are working in a capacity to better understand the COVID-19 pandemic using data and data science in the healthcare, biotech, pharma and other related industries
  • If you are working for a government agency or NGO seeking to better understand the COVID-19 pandemic using data and data science

Please apply here for your pass

 Our goal is to make as many passes available as can be handled by our livestream license agreements etc. Thus passes will be dispensed on a first come, first serve basis. Thank you for your understanding.   

Discounts

We offer academic, government, non-profit and start-up discounts.

To find out more please click HERE

Group Discounts

We offer group discounts for groups between 3 and 12 people. Please click for a purchase HERE.

If you have a group of 13 or more, please email us at group@odsc.com to enquire about additional discounts. Please mention the size of your group and the types of passes required.

Volunteer

In exchange for a free pass, ODSC is seeking volunteers to help with our program and event planning.  See more details HERE.

Where Business Meets AI

Ai x Business Summit

Co-located at ODSC East, Ai x brings together the leading practitioners, innovation experts, and business professionals that drive artificial intelligence across a range of industries

Ai x Finance 

Discover how techniques from Machine Learning, Deep Learning, and Predictive Analytics are driving Innovation in Finance

Ai x Healthcare

Gain AI expertise and learn from leading experts how to work with the frameworks and tools employed in AI for Healthcare

Ai x Retail

Learn to manage and deploy AI in the world of online retail. Hear from AI online retail management and heads of data science teams on a range of online retail AI topics

Ai x Network

Network with the AI experts, innovators, business professionals, and data scientists building the future of AI in finance, retail, healthcare, biotech, pharma, marketing and more..

Learn more

AI EXPO PARTNERS

Limited Booths Availability

Join ODSC East Expo

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See Who Attends ODSC East 2020


Why Attend ODSC

Accelerate your data science knowledge with the latest topics, tools, and trends presented by the best practitioners in the field

5 Reasons Why ODSC is a Better Experience

  • Looking for a conference that charges high ticket prices coupled mostly with vendor pitches that have zero relevance to you or your business? That’s not us 

  • We have a relentless focus on the best, most relevant content for our audience. Sure we have partners, but we limit their number and make sure they’re relevant 

  • Our focus is on the data science community and our contribution to that community’s growth and development, and on helping you, our attendee, gain relevant skills

  • As an applied data conference, we are committed to bringing you the most relevant topics and research that can have a direct impact on your work

  • We have fantastic networking activities at our events, so if you like your data science with a side of fun, we got you covered

Better Content & Training

  • Gain in-demand skills to enhance your data science career or simply become a better data scientist

  • Many topics to choose from, including 70+ talks, 27 workshops, and 20 training sessions all under one roof

  • Learn from the best and brightest in AI and data science to accelerate your learning and insights

  • Learn from the core contributors behind hugely popular tools such as scikit-learn and Caffe

Better Networking

  • Connect with 4,500 fellow data scientists, presenters, innovators, practitioners, and influencers

  • Get hired by innovative companies ranging from Fortune 500s to startups at our Data Science Career Fair

  • Meet executives from multiple industries using AI and data science to transform their industries

  • Attend multiple networking events including breaks, lunches, and evening receptions

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ODSC Newsletter

Stay up-to-date with the latest news and updates in open source data science. In addition, we’ll inform you about our many upcoming events in Boston, NYC, San Francisco, and London. And keep a lookout for special discount codes, only available to our newsletter subscribers!


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