Getting Started with AI on Jetson Nano (GSJN) – Outline

Detailed 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
  • Quiz Questions: Answer questions about what you've learned to reinforce your knowledge

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