Hands-on AI Training at GTC

TRAINING AT GTC 2020

The NVIDIA Deep Learning Institute (DLI) will host 60+ instructor-led training sessions, 30+ self-paced courses, and 6 full-day workshops offering developer certification at GTC 2020.  

Developers, data scientists, and researchers will learn how to apply deep learning and accelerated computing to solve the world’s most challenging problems in autonomous vehicles, robotics, digital content creation, healthcare, industrial inspection and more.

GTC 2019 training attendees can access instructor-led training content through March 2020 for any sessions attended. You can also access self-paced courses started onsite. Log into your NVIDIA Developer Program account at  courses.nvidia.com/join.

Instructor-led Workshops

All workshops take place on Sunday, March 22 from 9:00 - 17:00

Get access to a GPU-accelerated server in the cloud to complete hands-on exercises alongside other developers and earn a certificate in AI or accelerated computing.

Fundamentals of Accelerated Computing with CUDA C/C++

Fundamentals of Accelerated Computing with CUDA C/C++

Prerequisites: Basic C/C++ competency including familiarity with variable types, loops, conditional statements, functions, and array manipulations.
Technologies: C/C++, CUDA

The CUDA computing platform enables the acceleration of CPU-only applications to run on the world’s fastest massively parallel GPUs.

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Fundamentals of Accelerated Data Science with RAPIDS

Prerequisites: Experience with Python, ideally including pandas and NumPy
Technologies: RAPIDS, NumPy, XGBoost, DBSCAN, K-Means, SSSP, Python

RAPIDS is a collection of data science libraries that allows end-to-end GPU acceleration for data science workflows. In this training, you'll:

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Fundamentals of Accelerated Data Science with RAPIDS
Applications of AI for Predictive Maintenance

Applications of AI for Predictive Maintenance

Prerequisites: Experience with CNNs and C++
Technologies: TensorFlow, TensorRT, Python, CUDA C++, DIGITS

Learn how to design, train, and deploy deep neural networks for autonomous vehicles using the NVIDIA DRIVE™ development platform.

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Fundamentals of Deep Learning for Multi-Gpus

Prerequisites: Experience with stochastic gradient descent mechanics, network architecture, and parallel computing
Technologies:
TensorFlow

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 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.

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Fundamentals of Deep Learning for Multi-Gpus
Applications of AI for Anomaly Detection

Applications of AI for Anomaly Detection

Prerequisites: Experience with CNNs and Python
Technologies: RAPIDS, Keras, GANs, XGBoost

The amount of information moving through our world’s telecommunications infrastructure makes it one of the most complex and dynamic systems that humanity has ever built. In this workshop, you’ll implement multiple AI-based solutions to solve an important telecommunications problem: identifying network intrusions.

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Deep Learning for Autonomous Vehicles - Perception

Prerequisites: Experience with CNNs and C++
Technologies: TensorFlow, TensorRT, Python, CUDA C++, DIGITS

Learn how to design, train, and deploy deep neural networks for autonomous vehicles using the NVIDIA DRIVE™ development platform.

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Deep Learning for Autonomous Vehicles - Perception

Deep Learning Institute Workshops

Add one of these full-day, Sunday, March 22 workshops to your GTC pass.

DEEP LEARNING INSTITUTE WORKSHOPS RATE PER WORKSHOP
FUNDAMENTALS OF DEEP LEARNING FOR MULTI-GPUS
 
$375
FUNDAMENTALS OF ACCELERATED COMPUTING WITH CUDA C/C++
 
$375
FUNDAMENTALS OF ACCELERATED DATA SCIENCE WITH RAPIDS
 
$375
DEEP LEARNING FOR AUTONOMOUS VEHICLES - PERCEPTION
 
SOLD OUT
APPLICATIONS OF AI FOR ANOMALY DETECTION
 
$375
APPLICATIONS OF AI FOR PREDICTIVE MAINTENANCE
 
$375

Instructor-led Training Sessions

DLI will host two-hour, instructor-led training sessions on March 23-26 for Conference and Training passholders. Here are a few popular hands-on sessions:

Optimization and Deployment of TensorFlow Models with TensorRT

Learn the fundamentals of generating high-performance deep learning models in the TensorFlow platform using built-in TensorRT library (TF-TRT) and Python.

Introduction to CUDA Python with Numba

Explore how to use Numba to accelerate NumPy ufuncs in your Python code and write custom CUDA kernels in Python.

Deep Autoencoders for Recommendation Systems

Learn how to build recommendation systems for your customers using deep autoencoders.

WANT MORE TRAINING?

The NVIDIA Deep Learning Institute offers self-paced, online training powered by GPU-accelerated workstations in the cloud and instructor-led workshops onsite by request.