Introduction to IoT with Edge Devices, Sensors & S/Protocols

Learn IoT with Edge Devices, Sensors and Real-World Applications in Smart Cities, Industrial Automation & Robotics

What you'll learn
- Understand the difference between IoT, Edge Computing and Edge Machine Learning
- Explore the different types of Input & Output Devices
- Recognize the different type of pins on an Edge device - Power, Analog, Digital & PWM
- Understand the working of an Analog-to-Digital-Converter (ADC)
- Deep dive into the working of different serial protocols - UART, SPI and I2C
- Delve into the working and real-world use cases of 9 different sensors - vision, humidity, radiation, gas etc.
- Compare & contrast 5 popular edge devices like Arduino Nano 33 BLE Sense, Raspberry Pi 5 etc.
- Explore TinyML and understand how it differs from Edge Machine Learning

Requirements
- No prior knowledge of electronics/engineering needed. You will learn everything you need to know.

Description
Are you ready to dive into the exciting world ofInternet of Things (IoT)andEdge AI?

This beginner-friendly course provides acomplete introduction to IoT systems, focusing onedge computing, sensors, edge devices, andTinyML— the cutting-edge technology enabling machine learning on low-power devices.

Whether you're a student, developer, or tech enthusiast, this course willequip you with practical skillsto build real-world IoT applications insmart cities, healthcare, agriculture, automation,and beyond.

Disclaimer: This course contains the use of artificial intelligence.

What You’ll Learn

By the end of this course, you will:

Understand the architecture of IoT systems and the role of sensors, edge devices, and communication protocols

Learn how to choose the rightsensor(e.g., vision, gas, temperature, motion) based on use case requirements

Explore and compare differentedge deviceslike Arduino Nano 33 BLE Sense, Nicla Vision, OpenMV Cam H7 Plus, Portenta H7, and Raspberry Pi 5

Learn howserial protocolsenable communication between IoT components and ensure data transmission reliability

Real-World Applications Covered

We don't just teach theory — we bring it to life withreal-world applications, including:

Security & Surveillance: Detect intrusions, and reduce traffic violations using vision and motion sensors

Healthcare: Monitor patient vitals, detect fall events, and enable smarter elder care through wearable sensors and edge ML

Agriculture & Aquaculture: Automate watering, detect pests or fish feeding patterns using camera-based edge AI

Smart Cities: Use vision sensors for traffic flow optimization, toll automation, air quality monitoring, and forest fire alerts

Industrial Automation: Monitor asset performance, predict failures, and improve supply chain efficiency

Edge Devices You’ll Explore

Arduino ecosystem (Nano 33 BLE, Nicla Vision, Portenta H7)

OpenMV Cam H7 Plus

Raspberry Pi 5

Why Take This Course?

Google-optimized learning: Our curriculum is packed with trending tech keywords to help you stand out in job searches and projects

Comprehensive and beginner-friendly: No prior experience needed! Learn step-by-step through explanations and real-world examples

Future-proof your skills: Edge AI and TinyML are rapidly growing—get ahead of the curve with this foundational course

Fun & Easy to Follow: Our AI-generated audio brings lessons to life, making content more enjoyable and easier to absorb every step of the way

Join us and take yourfirst step toward becoming an IoT innovator. Whether you're looking to buildsmart devices, exploreEdge AI, or createimpactful tech solutions, this course will give you the tools and confidence to succeed!

Who this course is for:
- Graduates/Young professionals/Startup founders interested in IoT, Edge Computing or Edge Machine Learning
- Graduates/Young professionals/Startup founders interested in Self-driving cars, Drones or Robotics
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