Getting Started with AI

 

About this Course

The power of AI is now in the hands of makers, self-taught developers, and embedded technology enthusiasts everywhere with the NVIDIA Jetson developer kits. This easy-to-use, powerful computer lets you run multiple neural networks in parallel for applications like image classification, object detection, segmentation, and speech processing. In this course, you'll use Jupyter iPython notebooks on your own Jetson to build a deep learning classification project with computer vision models.

Required Hardware

Supported Jetson Developer Kit:

NVIDIA Jetson Orin Nano Developer Kit

NVIDIA Jetson AGX Orin Developer Kit

NVIDIA Jetson Nano Developer Kit

NVIDIA Jetson 2G Nano Developer Kit

Learning Objectives

You'll learn how to:

• Set up your NVIDIA Jetson Nano and camera
• Collect image data for classification models
• Annotate image data for regression models
• Train a neural network on your data to create your own models
• Run inference on the NVIDIA Jetson Nano with the models you create

Upon completion, you'll be able to create your own deep learning classification and regression models with the Jetson Nano.

Topics Covered

Tools and frameworks used in this course include PyTorch and NVIDIA Jetson Nano.

Course Outline

1. Setting up your Jetson Nano

Step-by-step guide to set up your hardware and software for the course projects

Introduction and Setup

Video walk-through and instructions for setting up JetPack and what items you need to get started

Cameras

Details on how to connect your camera to the Jetson Nano Developer Kit

Headless Device Mode

Video walk-through and instructions for running the Docker container for the course using headless device mode (remotely from your computer).

Hello Camera

How to test your camera with an interactive Jupyter notebook on the Jetson Nano Developer Kit

JupyterLab

A brief introduction to the JupyterLab interface and notebooks

2. Image Classification

Background information and instructions to create projects that classify images using Deep Learning

AI and Deep Learning

A brief overview of Deep Learning and how it relates to Artificial Intelligence (AI)

Convolutional Neural Networks (CNNs)

An introduction to the dominant class of artificial neural networks for computer vision tasks

ResNet-18

Specifics on the ResNet-18 network architecture used in the class projects

Thumbs Project

Video walk-through and instructions to work with the interactive image classification notebook to create your first project

Emotions Project

Build a new project with the same classification notebook to detect emotions from facial expressions

3. Image Regression

Instructions to create projects that can localize and track image features in a live camera image

Classification vs. Regression

With a few changes, the Classification model can be converted to a Regression model

Face XY Project

Video walk-through and instructions to build a project that finds the coordinates of facial features

Quiz Questions

Answer questions about what you've learned to reinforce your knowledge

Course Details

Duration: 08:00

Price: Free

Level: Technical - Beginner

Subject: Deep Learning

Language: English

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

Related Training:

You may be interested in the following free self-paced training on Jetson:

Free Courses : Getting Started with AI