Intel® Edge AI for IoT Developers Nanodegree v1.0.0

Nanodegree key: nd131

Version: 1.0.0

Locale: en-us

In this Nanodegree program, you will learn how to develop and optimize Edge AI systems, using Intel’s® OpenVINO™ toolkit.

Content

Part 01 : Welcome to the Program

Before diving into the program, let's first find out more about what taking a Udacity Nanodegree program is like and what it takes to succeed. We'll also cover software requirements and pre-requisites.

Module 01: Nanodegree Program Orientation
- Lesson 01: Nanodegree Program Introduction
  Before diving into the program, let's first find out more about what taking a Udacity Nanodegree program is like and how to succeed. We'll also cover software requirements and pre-requisites.

Part 02 : Edge AI Fundamentals with OpenVINO™

Welcome to Edge AI Fundamentals with OpenVINO™, where you'll learn about the basics of AI at the Edge, leverage pre-trained models available with the Intel® Distribution of OpenVINO Toolkit™, convert and optimize other models with the Model Optimizer, and perform inference with the Inference Engine. Additionally, you'll learn some additional topics for edge applications, like MQTT and how to stream video to servers.

Module 01: Edge AI Fundamentals with OpenVINO™
- Lesson 01: Introduction to AI at the Edge
  Get introduced to AI at the Edge, and find out about the topics you’ll learn throughout the rest of the course.
- Lesson 02: Leveraging Pre-Trained Models
  Utilize Pre-Trained Models from the Intel® Distribution of OpenVINO™ Toolkit to build powerful edge applications, without the need to train your own model.
- Lesson 03: The Model Optimizer
  Explore the Model Optimizer, which allows you to take models trained with many different Deep Learning frameworks and create an Intermediate Representation useful with the Inference Engine.
- Lesson 04: The Inference Engine
  Dive deeper into the Inference Engine, and perform inference in the OpenVINO™ Toolkit. By the end, you’ll know the full workflow for OpenVINO™ fundamentals and be ready to integrate into an app.
- Lesson 05: Deploying an Edge App
  With the OpenVINO™ Toolkit fundamentals down, you’re ready to move onto more topics to get your edge app up and running. Learn about handling input streams, MQTT and more as you finish the course!
- Lesson 06: Project: Deploy a People Counter App at the Edge
  Show off your new skills by deploying a people counter app at the edge! Go through the full OpenVINO™ Toolkit workflow, along with handling video streams and sending data with MQTT to build your app.
  
  Project Description - Deploy a People Counter App at the Edge
  
  Project Rubric - Deploy a People Counter App at the Edge
- Lesson 07: Optimize Your GitHub Profile
  Other professionals are collaborating on GitHub and growing their network. Submit your profile to ensure your profile is on par with leaders in your field.
  
  Project Description - Optimize Your GitHub Profile
  
  Project Rubric - Optimize Your GitHub Profile

Part 03 : Choosing the Right Hardware

Grow your expertise in choosing the right hardware. Identify key hardware specifications of various
hardware types (CPU, VPU, FPGA, and Integrated GPU). Utilize the DevCloud to test model performance
and deploy power-efficient deep neural network inference on on the various hardware types. Finally, you
will distribute workload on available compute devices in order to improve model performance.

Module 01: Choosing the Right Hardware
- Lesson 01: Introduction to Hardware at the Edge
  Learn about the key hardware types used on IoT devices and the basics of designing an Edge AI system.
- Lesson 02: CPUs and Integrated GPUs
  Use the Intel® Devcloud for the Edge for running deep learning models on the CPU and Integrated GPU.
- Lesson 03: VPUs
  Identify the key specifications of Intel® VPUs and use the Intel® DevCloud for the Edge to run deep learning models on the VPU.
- Lesson 04: FPGAs
  Identify the key specifications of Intel® FPGAs and utilize the HETERO Plugin to enable efficient hardware utilization.
- Lesson 05: Project: Smart Queuing System
  Given real-world scenarios to build a queuing system, use your knowledge of hardware specifications to identify which hardware types work best, and then test the application using the Intel® DevCloud.
  
  Project Description - Smart Queuing System
  
  Project Rubric - Smart Queuing System
- Lesson 06: Take 30 Min to Improve your LinkedIn
  Find your next job or connect with industry peers on LinkedIn. Ensure your profile attracts relevant leads that will grow your professional network.
  
  Project Description - Improve Your LinkedIn Profile
  
  Project Rubric - Improve Your LinkedIn Profile

Part 04 : Optimization Techniques and Tools

Learn how to optimize your model and application code to reduce inference time when running your
model at the edge. Use different software optimization techniques to improve the inference time of your
model. Calculate how computationally expensive your model is. Use DL Workbench to optimize your
model and benchmark the performance of your model. Use a VTune amplifier to find and fix hotspots in
your application code. Finally, package your application code and data so that it can be easily deployed to
multiple devices.

Module 01: Optimization Techniques and Tools
- Lesson 01: Introduction to Software Optimization
  This lesson introduces software optimization (SO), when and why you should use it, and the broad classes of SO algorithms
- Lesson 02: Reducing Model Operations
  Implement optimization techniques that improve performance by reducing the number of model operations.
- Lesson 03: Reducing Model Size
  One of the ways to perform software optimization is to reduce the size of the model. In this lesson you will learn about the different algorithms used to do that.
- Lesson 04: Other Optimization Tools and Techniques
  Use VTune Amplifier to measure hotspots in your application code.
- Lesson 05: Project: Computer Pointer Controller
  Demonstrate your ability to run multiple models in the OpenVINO toolkit on the same machine to control your computer pointer using your eye gaze.
  
  Project Description - Computer Pointer Controller
  
  Project Rubric - Computer Pointer Controller