Hands-on Training in AI

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 5 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.

DEEP LEARNING FOR
INDUSTRIAL INSPECTION

Prerequisites: Experience with Python and convolutional neural networks (CNNs)

Certification available

Learn how to design, train, test, and deploy building blocks of a hardware-accelerated industrial inspection pipeline. You'll build a deep learning model to automate the verification of capacitors in NVIDIA's printed circuit board (PCB) using a real production dataset.
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DEEP LEARNING FOR ROBOTICS

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

Certification 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

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

Certification 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

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

Certification 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

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

Certification 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. Full schedule coming soon.

 

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.

FUNDAMENTALS OF ACCELERATED COMPUTING WITH CUDA PYTHON

Prerequisites: Basic experience with Python and NumPy
Duration: 6 hours

Get hands-on with Numba - the just-in-time, type-specializing Pythong function compiler - to acelerate Python programs to run on massively parallel NVIDIA GPUs.

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.