Hands-on Training in AI

WORKSHOPS & SUMMIT NOV. 4, 2019
SESSIONS & EXHIBITS NOV. 5 - 6, 2019

Explore Courses in Deep Learning and Accelerated Computing

Get the hands-on experience you need to transform the future of artificial intelligence with the NVIDIA Deep Learning Institute (DLI). Learn how to apply deep learning, data science, and accelerated computing to solve the most challenging problems faced by government and industries like defense and healthcare.

Government attendees receive a free conference pass and save 50% on training (except DLI workshops).

University and non-profit attendees save 50% on conference and conference and training passes (no offers can be combined with DLI workshops).

INSTRUCTOR-LED DLI WORKSHOPS

Attend one of 7 full-day workshops led by DLI certified instructors on Monday, November 4th. You can earn a certificate of competency by completing the built-in assessment. Workshops are open to attendees with a DLI Workshop Pass.

Fundamentals of Accelerated Data Science with RAPIDS

FUNDAMENTALS OF ACCELERATED DATA SCIENCE WITH RAPIDS

Prerequisites: Experience with Python, ideally including Pandas and NumPy.

Certificate available


Get hands-on with the RAPIDS data science platform that enables end-to-end GPU acceleration for data science workflows. You'll learn how to use GPUs to perform data analysis at massive scale by applying machine learning and network analytics to real-world, substantive problems. The exercises will combine tabular, textual, geospatial, and network data to solve complex use cases.

GETTING STARTED WITH AI ON JETSON NANO

GETTING STARTED WITH AI ON JETSON NANO

Prerequisites: Basic familiarity with Python (helpful, not required).

Certificate available

Explore how to build a deep learning classification project with computer vision models using your NVIDIA Jetson Nano Developer Kit. This is a guided learning experience where you'll complete the course at your own pace with experts in the room. Registration includes your own Jetson Nano Developer Kit, a pre-loaded SD card, camera, and all required hardware to optimize your training experience and continue learning afterward.

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DEEP LEARNING FOR ROBOTICS

DEEP LEARNING FOR ROBOTICS

Prerequisites: Basic familiarity with deep neural networks, basic coding experience in Python or similar language.

Certificate available

Explore how to create robotics solutions on an NVIDIA Jetson for embedded applications. You’ll learn how to integrate computer vision into the robot’s operating system, so it can autonomously detect an object and move toward it.

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DEEP LEARNING FOR INTELLIGENT VIDEO ANALYTICS

DEEP LEARNING FOR INTELLIGENT VIDEO ANALYTICS

Prerequisites: Experience with deep networks (specifically variations of CNNs), intermediate-level experience with C and Python.

Certificate available

With the rise in traffic cameras, autonomous vehicles, and smart cities, there's a demand for faster and more efficient object detection and tracking models. Learn how to design, train, and deploy building blocks of a hardware-accelerated traffic management system based on parking lot camera feeds.

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DEEP LEARNING FOR HEALTHCARE IMAGE ANALYSIS

DEEP LEARNING FOR HEALTHCARE IMAGE ANALYSIS

Prerequisites: Basic familiarity with deep neural networks, basic coding experience in Python or a similar language.

Certificate available

Explore how to apply convolutional neural networks (CNNs) to MRI scans to perform a variety of medical tasks and calculations.

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FUNDAMENTALS OF ACCELERATED COMPUTING WITH CUDA PYTHON

FUNDAMENTALS OF ACCELERATED COMPUTING WITH CUDA PYTHON

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.

Certificate available

Learn how to use Numba—the just-in-time, type-specializing Python function compiler—to accelerate Python programs to run on massively parallel NVIDIA GPUs.

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INSTRUCTOR-LED TRAINING SESSIONS

Join instructor-led training sessions on deep learning, data science, and accelerated computing on November 5th and 6th. Led by DLI certified instructors, these two-hour training sessions will teach you how to apply specific concepts or techniques to your work. Training sessions are open to attendees with a GTC Conference and Training Pass.

Here are a few popular sessions.

 

Accelerating Data Science Workflows with RAPIDS

Learn to build a GPU-accelerated, end-to-end data science workflow using RAPIDS open-source libraries for massive performance gains. Professional competency with Pandas, NumPy, and scikit-learn required.

Optimization and Deployment of TensorFlow Models with TensorRT

Learn how to optimize TensorFlow models to generate fast inference engines in the deployment stage. Experience with TensorFlow and Python required.

Introduction to CUDA Python with Numba

Explore how to use Numba to GPU-accelerate NumPy ufuncs in your Python code and how to write custom CUDA kernels in Python. Basic Python and Numpy competency required.

SELF-PACED TRAINING

Get started on DLI self-paced training on deep learning, data science, and accelerated computing on November 5th and 6th during conference hours. All GTC attendees are welcome – no special pass required.

NEURAL NETWORK DEPLOYMENT WITH DIGITS AND TENSORRT

Prerequisites: Basic experience with neural networks
Duration: 2 hours

Learn to deploy deep learning to applications that recognize images and detect pedestrians in real-time.

IMAGE SEGMENTATION WITH TENSORFLOW

Prerequisites: Basic experience with neural networks
Duration: 2 hours

Explore how to segment MRI images to measure parts of the heart by experimenting with TensorFlow tools such as TensorBoard and the TensorFlow Python API.

WANT MORE TRAINING?

The NVIDIA Deep Learning Institute offers hands-on training for developers, data scientists, and researchers looking to solve the world’s most challenging problems with deep learning and accelerated computing.