Discover Deep Learning with Nvidia’s Robotics Workshop on April 17

Nvidia is partnering with TechCrunch Sessions: Robotics + AI to host a pre-conference workshop at UC Berkeley on April 17 titled Deep Learning for Robotics.

In this eight-hour, instructor-led workshop you’ll get an overview of the Robot Operating System(ROS) and its associated architecture, followed by hands-on simulation and coding experience using a live GPU-accelerated environment. At the end of completing your assessment, you’ll get an Nvidia Deep Learning Institute certificate. Learn more about the workshop here.

Learning Objectives

• Learn the general ROS paradigm of messages passing between nodes
• Learn to work with the robotic development workflow by taking a hands-on approach to simulation, development and deployment using a Gazebo simulator
• Learn to integrate an object detection inference model, trained with DIGITS, into a ROS network to build autonomous behavior for a Jetson-based robot

Why Deep Learning Institute Hands-on Training?

• Learn how to build deep learning and accelerated computing applications across a wide range of industry segments, such as autonomous vehicles, digital content creation, finance, game development, healthcare and more
• Benefit from guided hands-on experience using the widely used, industry-standard software, tools and frameworks
• Gain real-world expertise through content designed in collaboration with industry leaders such as the Children’s Hospital Los Angeles, Mayo Clinic and PwC
• Earn a DLI certificate to demonstrate your subject matter competency and support professional career growth
• Access content anywhere, anytime with a fully configured, GPU-accelerated workstation in the cloud

Prerequisites:
Experience with deep neural networks (specifically variations of CNNs) and intermediate-level experience Python. Knowledge of Linux and C++ is helpful but not required.

Tickets are on sale now for $299 (normally $500) for this immersive workshop. Seating is limited, book your ticket today before we sell out.