YoVDO

NVIDIA DeepStream development with Microsoft Azure

Offered By: Microsoft via Microsoft Learn

Tags

Microsoft Azure Courses Machine Learning Courses Cloud Computing Courses Edge Computing Courses Containerization Courses

Course Description

Overview

  • Module 1: Learn how to set up and configure an x86-based Ubuntu 18.04 system to host an NVIDIA DeepStream development environment.

    • In this module, you'll learn how to:

    • Describe the components of Intelligent Video Analytics applications
    • Install the NVIDIA DeepStream SDK and dependencies onto an x86 host
    • Run NVIDIA DeepStream applications
    • Modify NVIDIA DeepStream application configurations
  • Module 2: Learn how to set up and configure the NVIDIA DeepStream 6.0 Graph Composer on an x86-based Ubuntu 18.04 system to enable rapid development of Intelligent Video Analytics application pipelines for deployment to cloud and edge-capable devices.

    • In this module, you'll learn how to:

    • Install the DeepStream Graph Composer application and reference graphs.
    • Develop Intelligent Video Analytics applications by using the DeepStream Graph Composer.
    • Package DeepStream Graph Composer applications into a container by using container-builder.
    • Publish DeepStream Graph Composer container workloads into Azure Container Registry for secure redistribution.
  • Module 3: Learn how to publish and deploy an ARM-based DeepStream container workload to NVIDIA embedded hardware using Azure IoT Edge.

    • In this module, you will learn how to:

    • Modify a DeepStream Graph Composer application to publish data to a hub in Azure IoT Hub.
    • Build and publish cross-platform DeepStream container images to a container registry in Azure Container Registry.
    • Configure Azure IoT Edge to run on NVIDIA embedded hardware.
    • Deploy cross-platform DeepStream images to NVIDIA embedded devices by using Azure IoT Edge.

Syllabus

  • Module 1: Set up and configure an NVIDIA DeepStream development environment
    • Introduction
    • Introduction to Intelligent Video Analytics
    • Exercise - Install the NVIDIA DeepStream dependencies and SDK
    • Exercise - Run an NVIDIA DeepStream sample application
    • Exercise - Modify the DeepStream sample applications
    • Knowledge check
    • Summary
  • Module 2: Introduction to NVIDIA DeepStream Graph Composer with Microsoft Azure
    • Introduction
    • Introduction to the NVIDIA DeepStream Graph Composer
    • Exercise - Install NVIDIA DeepStream Graph Composer
    • Exercise - Run an NVIDIA DeepStream Graph Composer reference application
    • Exercise - Package an NVIDIA DeepStream Graph Composer application into a containerized workload
    • Exercise - Publish an NVIDIA DeepStream Graph Composer container to Azure Container Registry
    • Knowledge check
    • Summary
  • Module 3: NVIDIA DeepStream embedded device deployment with Azure
    • Introduction
    • Introduction to AI at the edge with NVIDIA Jetson and Azure
    • Exercise - Configure DeepStream Graph Composer to publish data to Azure IoT Hub
    • Exercise - Build and publish cross-platform DeepStream container images
    • Exercise - Configure Azure IoT Edge on NVIDIA embedded hardware
    • Exercise - Deploy cross-platform DeepStream images to NVIDIA embedded devices with Azure IoT Edge
    • Knowledge check
    • Summary

Tags

Related Courses

Software as a Service
University of California, Berkeley via Coursera Software Defined Networking
Georgia Institute of Technology via Coursera Pattern-Oriented Software Architectures: Programming Mobile Services for Android Handheld Systems
Vanderbilt University via Coursera Web-Technologien
openHPI Données et services numériques, dans le nuage et ailleurs
Certificat informatique et internet via France Université Numerique