IoT Developer (Beginner, Onsite Course)

Course content

1. Introduction to IoT: Concepts and Applications
   Overview of IoT, its components, architecture, and real-world applications.
2. Setting Up Your IoT Development Environment
   Installing tools like Arduino IDE, setting up Raspberry Pi, and basic hardware requirements.
3. Basic Electronics for IoT
   Understanding electronic components: resistors, capacitors, transistors, and basic circuits.
4. Introduction to Microcontrollers and Microprocessors
   Overview of microcontrollers (Arduino) and microprocessors (Raspberry Pi) in IoT systems.
5. Programming Basics for IoT with Arduino
   Writing basic programs for Arduino using C/C++, controlling LEDs, and reading sensor inputs.
6. Sensors and Actuators in IoT
   Understanding sensors (temperature, humidity, motion) and actuators (motors, relays), their working principles, and interfacing with Arduino.
7. IoT Communication Protocols
   Introduction to protocols like MQTT, HTTP, and CoAP for device communication.
8. Wireless Communication: Wi-Fi and Bluetooth
   Working with Wi-Fi and Bluetooth modules for wireless IoT communication.
9. Introduction to Raspberry Pi and Python Programming
   Setting up Raspberry Pi and using Python for basic IoT tasks.
10. Interfacing Sensors with Raspberry Pi
    Reading sensor data and controlling outputs with Raspberry Pi using Python.
11. Cloud Platforms for IoT: Overview
    Introduction to cloud platforms like AWS IoT, Google Cloud IoT, and ThingSpeak for IoT data storage and analysis.
12. Data Logging and Visualization
    Collecting data from sensors and visualizing it using tools like Matplotlib or cloud dashboards.
13. IoT Security Basics
    Overview of security challenges in IoT systems and basic protection mechanisms like encryption and secure communication.
14. Building a Simple IoT Project with Arduino
    Hands-on project: Building a simple IoT system to collect and display sensor data over Wi-Fi.
15. Introduction to Edge Computing in IoT
    Basics of edge computing and how it can enhance IoT systems by reducing latency and dependency on cloud services.
16. Deploying IoT Systems: Connecting Devices to the Cloud
    Final project: Connecting an IoT device to the cloud, sending data, and visualizing it on a dashboard.

Capstone Project

1. Smart Plant Monitor: Develop a system that uses sensors to monitor soil moisture and light levels, employing machine learning to predict when plants need watering or additional light.
2. AI-Powered Home Security System: Create a basic home security system using cameras and motion sensors that utilize AI for object detection to differentiate between pets, humans, and potential intruders.
3. Energy-Efficient Smart Thermostat: Design a smart thermostat that learns user preferences and optimizes heating and cooling schedules using machine learning to save energy.
4. Intelligent Waste Management System: Build a system that uses IoT sensors to monitor waste bin levels and employs AI to optimize collection routes based on real-time data.
5. Predictive Maintenance for IoT Devices: Develop a simple predictive maintenance system that monitors the performance of a small appliance (like a fan or pump) and uses machine learning to predict when maintenance is needed based on usage patterns.

Course Detail : https://iroschool.org/iot-developer/