Artificial Intelligence Computing Leadership from NVIDIA

The Opening Keynote by NVIDIA CEO Jensen Huang is Monday, March 18 at 2 PM

Register for a Conference & Training, Conference, or Exhibits pass. You can also add a March 17 DLI Workshop for $350.

ACADEMIC, GOVERNMENT & NON-PROFIT SAVINGS Receive a 50% discount when you register with a university, government, or non-profit email address. Must present credentials at check-in to receive badge.

GROUP SAVINGS Purchase 5 or more of the same pass type to receive a 25% discount when you register.

Add one of these full-day, Sunday, March 17 workshops to your GTC pass.

Prerequisites: Basic Python competency including familiarity with variable types, loops, conditional statements, functions, and array manipulations. NumPy competency including the use of ndarrays and ufuncs. CUDA programming knowledge is not required. Assessment Type: Code-based Certification available

This workshop explores how to use Numba—the just-in-time, type-specializing Python function compiler—to accelerate Python programs to run on massively parallel NVIDIA GPUs. You’ll learn how to:

Upon completion, you’ll be able to use Numba to compile and launch CUDA kernels to accelerate your Python applications on NVIDIA GPUs.

The computational requirements of deep neural networks used to enable AI applications like self-driving cars are enormous. A single training cycle can take weeks on a single GPU, or even years for the larger datasets like those used in self-driving car research. Using multiple GPUs for deep learning can significantly shorten the time required to train lots of data, making solving complex problems with deep learning feasible. This workshop will teach you how to use multiple GPUs to training neural networks. You'll learn:

Upon completion, you'll be able to effectively parallelize training of deep neural networks using TensorFlow.

Prerequisites: Basic experience with neural networks and Python programming, familiarity with linguistics Assessment Type: Code-based, multiple choice Frameworks: TensorFlow, Keras Certification available

Learn the latest deep learning techniques to understand textual input using natural language processing (NLP). You’ll learn how to:

Upon completion, you’ll be proficient in NLP using embeddings in similar applications.

Prerequisites: Basic experience with deep neural networks (specifically variations of CNNs) and intermediate-level experience with C++ and Python Assessment Type: Code-based Frameworks: TensorFlow Certification available

Smart cities collect huge amounts of video footage that require advanced deep learning techniques to transform data into actionable insights. The first step in more complex deep learning workflows is detecting specific types of objects. This involves identification, classification, segmentation, prediction, and recommendation. In this workshop, you’ll learn how to:

Upon completion, you’ll be able to deploy object detection and tracking networks to work on real-time, large-scale video streams.

Prerequisites: Basic experience with CNNs, circuits, and hardware Assessment Type: Code-based, multiple choice Frameworks Details coming soon Certification available

AI is revolutionizing the acceleration and development of robotics across a broad range of industries. Explore how to create robotics solutions on a Jetson for embedded applications. You’ll learn how to:

Upon completion, you’ll know how to deploy high-performance deep learning applications for robotics.

Prerequisites: Familiarity with basic programming, fundamentals such as functions and variables Assessment Type: Code-based Frameworks: Caffe, DIGITS Certification available

Explore the fundamentals of deep learning by training neural networks and using results to improve performance and capabilities.You'll learn how to solve real-world problems using deep learning.