Don't miss the boat!

Lead your team to MLOps excellence. Increase model velocity.
April 12-16, 2021

Chart your course today.


The chance to lead in SaaS? Big data? Hadoop? Those ships have already left the port. But for enterprise data science and MLOps, the time is now. Technologists and IT Leaders have a unique opportunity to take the reins, but you need to start educating yourself. Here's how to get started:

  1. Complete the short form on this page for your unique NVIDIA GTC registration link, and to be entered into our drawing for a free jet ski. 

  2. Attend any of the featured GTC sessions listed below. Take a screenshot -- you'll need this in order to claim the jet ski if you win.

  3. Check your email on April 17 to find out if you've won the jet ski. Either way, you'll leave the conference with a practical way to increase velocity and make waves -- either with MLOps in the workplace, or in the ocean.


Read the Sweepstakes Terms and Conditions.

Not interested in winning the jet ski but want to check out GTC? No problem -- skip the sweepstakes entry and go straight to GTC here.


GTC Speakers

Screen Shot 2021-03-11 at 11.18.34 AM
Jensen Huang
Founder, President & CEO, NVIDIA
Rima Alameddine
VP, Americas, Healthcare & Manufacturing, NVIDIA
swanson_jim-040720-002-cropped2-100838792-large (1)
Jim Swanson
CIO, Johnson & Johnson
Nick Elprin Headshot
Nick Elprin
Founder & CEO, Domino
Sean Otto, Ph D
Director of Analytics, The AES Corporation
Thomas Robinson
VP, Strategic Partnerships, Domino
Nikolay Manchev
Head of Data Science, EMEA, Domino
Kevin Flansburg
Kevin Flansburg
Senior Field Engineer, Domino
Sophie Watson_headshot
Sophie Watson
Principal Data Scientist, Red Hat
Andrew Modjeski
Andrew Modjeski
AI Applications Lead, Lockheed Martin

Attend any of these sessions for your chance to win a jet ski

Tuesday, April 13, 2021
(Times listed in PDT)
How Johnson & Johnson is embedding data science across their business [S33036]
What functional areas can IT own to streamline data science ops across teams? How can MLOps in the enterprise allow IT to control spending and governance while still enabling Model Velocity? How to generate quick wins as the Data Science function is set up for success? Find out in this session with Johnson & Johnson’s CIO Jim Swanson and Domino CEO Nick Elprin.
Thursday, April 15, 2021
(Times listed in PDT)
Running complex workloads using on-demand GPU-accelerated Spark/RAPIDS clusters [E32337]
Apache Spark is the de facto standard for processing large data sets and is increasingly being used for fitting and scoring complex machine learning models. GPU-accelerated worker nodes can substantially speed up the model training phase and simultaneously reduce costs (frequently by orders of magnitude). Although data scientists are usually comfortable using Spark through Scala, Python, and R, the complexity of provisioning and maintaining the Spark cluster can be considerable. In this session we present an integrated solution based on the Domino Data Science Platform, Nvidia NGC containers, and RAPIDS Accelerator for Apache Spark, which enables data scientists to easily provision a Spark/RAPIDS cluster with an arbitrary number of GPU-accelerated workers, and access it through their favourite IDE.
On-Demand Sessions Available April 12 at 10:00
(Times listed in PDT)
How to keep the F-35 flying [SS33119]
Learn about using the MATLAB machine/deep learning algorithm plus Domino test bench plus NVIDIA GPUs with Lockheed Martin's aeronautics team to drive performance in this fifth-generation fighter aircraft.
How AES went from zero to 50 deployed models in two years [SS33050]
In <2 years, AES built out a global team, its underlying infrastructure, and they’ve built and deployed 50+ models to date. Today, AES models optimize liquid gas shipping and logistics, predict when power generation equipment will need maintenance, guide fintech energy trades, make hydrology predictions, inform bids on power generation facilities, provide weather forecasting for utilities, and more. Their cloud infrastructure supports the diverse needs of data scientists, giving them access to compute resources (including NVIDIA Tesla) and tools (including SAS Viya and H2O) within a centralized Domino Data Lab platform for MLOps.
Visual target recognition from raw data to NVIDIA Jetson with MATLAB and Domino [SS33305]
Organizations looking to bring AI-driven capabilities to products often find out that the journey is fraught with challenges. Common hurdles include the need to invest in hardware and cloud capacity, algorithm complexity and explainability, the need for collaboration tools, and lack of a clear path to hardware deployment. Abhijit Bhattacharjee will walk through an end-to-end workflow powered by MathWorks, Domino Data Lab, and NVIDIA. Our goal will be to produce a working visual target recognition model, helping devices ‘understand’ their environment through computer vision. The demo will showcase how to: • Use MATLAB-based data acquisition and label automation tools. • Consume data collected in Domino. • Use Domino’s easy GPU access capability. • Train the deep learning model in MATLAB. • Download the model and generate NVIDIA CUDA code in MATLAB for direct deployment on Jetson.
Slash time spent on model training and tuning. Unleash multi-node GPUs! [SS33062]
Shorten the time it takes to train and tune complex, data-intensive models. Learn how to unleash the power of leading distributed execution frameworks, state-of-the-art machine learning libraries, and large-scale, multi-GPU computing clusters. Attendees will learn how to set up a network of NVIDIA compute nodes, and enable Infiniband/RDMA for high-performance data transfer to train and perform hyperparameter tuning on a deep neural network image classification model using Ray and PyTorch.
Democratizing access to powerful MLOps infrastructure [S32190]
Fast storage and powerful GPUs have broken through many barriers to data science and ML research in the past several years, but organizational and access issues still remain. Learn how the Domino MLOps platform provides easy access for researchers and data scientists to powerful AI research and training infrastructure. We will explore the combined solution of NetApp storage, NVIDIA GPUs, and Domino software to provide agile access to infrastructure while ensuring robust process and governance tools fit for enterprises.
NVIDIA GTC 2021 | Domino Data Lab

Watch. Learn. Make waves.

Complete this short form to receive your special GTC registration link and qualify for a chance to win a brand new jet ski.

The entry period for this form has ended. Please email us at with questions or concerns.