Get started with self-paced and instructor-led labs at GTC 2018.


Get the knowledge and hands-on experience you need to transform the future of artificial intelligence, deep learning, self-driving cars, accelerated computing, and more. Check out the instructor-led workshops and self-paced labs at GTC 2018, with access to experts from the NVIDIA Deep Learning Institute (DLI) and other leading organizations in the industry.


DLI will host four full-day technical workshops on Sunday, March 25 before GTC. Get hands-on with deep learning or accelerated computing, led by a DLI certified instructor. A special pass will be required for attendance.

Fundamentals of Deep Learning for Computer Vision

Prerequisite: None

Explore the fundamentals of deep learning by training and deploying neural networks. Upon completion, you’ll be able to start solving problems on your own with deep learning.

Fundamentals of Deep Learning for Natural Language Processing

Prerequisite: 'Fundamentals of Deep Learning for Computer Vision' or similar experience

Get hands-on with the latest techniques to understanding textual input using Natural Language Processing.

Perception for Autonomous Vehicles

Prerequisite: ‘Fundamentals of Deep Learning for Computer Vision’ or similar experience

Learn how to design, train, and deploy deep neural networks for autonomous vehicles using the NVIDIA DRIVE PX2 development platform.

Fundamentals of Accelerated Computing with CUDA C/C++

Prerequisite: None

Learn how to accelerate and optimize C/C++ CPU-only applications using essential CUDA tools and techniques.


Join other developers and researchers in hands-on, classroom-style workshops led by DLI certified instructors at GTC Lab capacity is limited. Register fast to reserve your spot.

Learn how to segment MRI images to measure parts of the heart with TensorFlow tools. Upon completion, you'll be able to set up most computer vision workflows using deep learning.

Learn how to track moving objects in large-scale video datasets through hands-on exercises that explore the strategies and trade-offs involved in developing high-quality neural network models. 

Learn about memory optimization techniques when programming with CUDA C/C++ on an NVIDIA GPU, and how to use the NVIDIA Visual Profiler (NVVP) to support these optimizations.


These labs are a unique opportunity to get hands-on with specific programming languages, technologies, and domains. There’s no need to schedule a self-paced lab. Just visit the Lower Level Concourse to get started. Each lab takes two hours to complete and laptops will be provided.

Here are a few popular self-paced labs:

Learn how to train a deep neural network to recognize handwritten digits.

Learn how to create datasets using electronic health records and model time-series data using RNNs.

Learn how to accelerate your C/C++ application using CUDA to harness the power of GPUs.

NVIDIA Deep Learning Institute


The NVIDIA Deep Learning Institute delivers hands-on training for developers, data scientists, and researchers looking to solve challenging problems with deep learning and accelerated computing. Through self-paced labs and instructor-led workshops, the Deep Learning Institute offers training on the latest techniques for designing, training, and deploying neural network-powered machine learning across a variety of application domains. The DLI also teaches you how to optimize your code for performance using NVIDIA CUDA® and OpenACC.