The problem is, leveraging ML with IoT has historically meant backhauling all your sensor data to the Cloud. When the cloud is involved, security is a concern, and in the realm of IoT, security is often a dirty word.

In this workshop, you’ll learn how to leverage the power of Machine Learning on Edge Devices and build secure, cloud-independent IoT applications.

Day 1

Section 1: The Basics of Machine Learning

Session 1: Demystifying AI, ML, etc.

• Lab 1: Building your first ML Model
• Session 2: ML models for Complex Data: CNNs and LSTMs
• Lab 2: Building a CNN for Image Recognition

Section 2: The Basics of IoT

• Session 1: Introducing the Blues Wireless Ecosystem
• Lab 1: Claiming your first Device
• Session 2: Working with Sensors and Actuators to collect data
• Lab 2: Working with Sensor Data

Day 2

Section 3: ML and the IoT

• Session 1: Why ML and the IoT
• Session 2: ML at the Edge with Single Board Computers (SBCs)
• Lab 2: Building ML Models for Edge Inferencing
• Lab 3: Inferencing on SBCs
• Session 3: ML at the Edge with Microcontrollers (MCUs)
• Lab 4: Building ML Models for Microcontrollers
• Lab 5: Inferencing on MCUs
  

Section 4: The future of ML and the IoT

• Session 4: What's next for ML on the Edge?
• Lab 1: Hacking Challenge and Free Exploration

Computer Setup

Attendees will need to bring a laptop with the following installed:

• Visual Studio Code - https://code.visualstudio.com/download
• PlatformIO IDE extension for VS Code - https://platformio.org/
• Python 3.6 or greater - https://python.org
• Node.js - https://nodejs.org
• Edge Impulse CLI (npm install -g edge-impulse-cli)
• Chromium-based web browser (e.g. latest version of Chrome, Edge, Brave)
• Set up a free account on Blues Wireless Notehub @ notehub.io
• Set up a free account on Edge Impulse Studio @ studio.edgeimpulse.com