IoT with python

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Module 1 – Python & IoT Fundamentals
  • Day 1: Introduction to IoT — concepts, real-world applications, hardware & software overview. Day 2: Python basics for IoT — variables, loops, functions, modules. Day 3: GPIO basics — how Python interacts with hardware pins. Day 4: Setting up Raspberry Pi (or ESP32 with MicroPython) and running first script. Day 5: Using Python libraries for hardware control (RPi.GPIO, gpiozero). Day 6: Reading data from simple sensors (temperature, humidity). Day 7: Mini Project: LED control with Python (on/off, blink patterns).
Module 2 – Sensors, Actuators & Data Handling
  • Day 8: Interfacing with multiple sensors (motion, light, gas). Day 9: Controlling actuators (motors, servos) with Python. Day 10: Data acquisition from IoT devices. Day 11: Storing IoT data in CSV, JSON, or SQLite database. Day 12: Real-time data visualization using matplotlib or Plotly. Day 13: Introduction to MQTT protocol for device communication. Day 14: Mini Project: Sensor data logger (logs temperature & humidity every minute).
Module 3 – Networking & Cloud Integration
  • Day 15: IoT networking basics — IP addressing, Wi-Fi setup. Day 16: Sending IoT data to cloud platforms (ThingSpeak, AWS IoT, Blynk). Day 17: Receiving commands from the cloud to control devices. Day 18: Building a web dashboard using Flask for IoT data. Day 19: Controlling IoT devices from a web/mobile interface. Day 20: IoT security basics — encrypting data & securing APIs. Day 21: Mini Project: Remote home automation (light & fan control over the internet).
Module 4 – Advanced IoT Applications & Capstone
  • Day 22: Edge computing — processing IoT data locally before sending to cloud. Day 23: Machine Learning on IoT devices (TensorFlow Lite). Day 24: Image processing with IoT cameras using OpenCV. Day 25: Voice control for IoT devices (Google Assistant, Alexa integration). Day 26: Energy-efficient IoT programming for battery-powered devices. Day 27: Strategies for scaling IoT projects (multiple devices, monitoring). Day 28: Capstone Planning — choose a project: Smart Home, Smart Farming, Industrial IoT. Day 29: Build & test the capstone project. Day 30: Deploy, document, and prepare project for portfolio.
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Course Detail
  • Week 1 – Python & IoT Fundamentals
    • Day 1: Introduction to IoT — concepts, real-world applications, hardware & software overview.
    • Day 2: Python basics for IoT — variables, loops, functions, modules.
    • Day 3: GPIO basics — how Python interacts with hardware pins.
    • Day 4: Setting up Raspberry Pi (or ESP32 with MicroPython) and running first script.
    • Day 5: Using Python libraries for hardware control (RPi.GPIO, gpiozero).
    • Day 6: Reading data from simple sensors (temperature, humidity).
    • Day 7: Mini Project: LED control with Python (on/off, blink patterns).
  • Week 2 – Sensors, Actuators & Data Handling
    • Day 8: Interfacing with multiple sensors (motion, light, gas).
    • Day 9: Controlling actuators (motors, servos) with Python.
    • Day 10: Data acquisition from IoT devices.
    • Day 11: Storing IoT data in CSV, JSON, or SQLite database.
    • Day 12: Real-time data visualization using matplotlib or Plotly.
    • Day 13: Introduction to MQTT protocol for device communication.
    • Day 14: Mini Project: Sensor data logger (logs temperature & humidity every minute).
  • Week 3 – Networking & Cloud Integration
    • Day 15: IoT networking basics — IP addressing, Wi-Fi setup.
    • Day 16: Sending IoT data to cloud platforms (ThingSpeak, AWS IoT, Blynk).
    • Day 17: Receiving commands from the cloud to control devices.
    • Day 18: Building a web dashboard using Flask for IoT data.
    • Day 19: Controlling IoT devices from a web/mobile interface.
    • Day 20: IoT security basics — encrypting data & securing APIs.
    • Day 21: Mini Project: Remote home automation (light & fan control over the internet).
  • Week 4 – Advanced IoT Applications & Capstone
    • Day 22: Edge computing — processing IoT data locally before sending to cloud.
    • Day 23: Machine Learning on IoT devices (TensorFlow Lite).
    • Day 24: Image processing with IoT cameras using OpenCV.
    • Day 25: Voice control for IoT devices (Google Assistant, Alexa integration).
    • Day 26: Energy-efficient IoT programming for battery-powered devices.
    • Day 27: Strategies for scaling IoT projects (multiple devices, monitoring).
    • Day 28: Capstone Planning — choose a project: Smart Home, Smart Farming, Industrial IoT.
    • Day 29: Build & test the capstone project.
    • Day 30: Deploy, document, and prepare project for portfolio.
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