[Udemy] IOT using NodeMCU(Powered by ESP8266), MicroPython & PyCharm

[Udemy] IOT using NodeMCU(Powered by ESP8266), MicroPython & PyCharm
Table of Contents
1

What are you going to do in this course

2

What is Internet Of Things ?

3

Hardware Required

4

Software Setup

5

Lab 1 - Blinking LEDs

6

Lab 2 - Pulse Width Modulation

7

Lab 3 - Reading onchip ADC

8

Lab 4 - Handling Vibration / Motion Sensor (SW420)

9

Lab 5 - Handling Temperature and Humidity Sensor(DHT11)

10

Lab 6 - Connecting NodeMCU to Internet & Watch StarWars Asciimations

11

Project 1 - Posting Vibration , Temp and Humidity Sensor Data to Thingspeak

12

Project 2 - Posting Vibration, Temp and Humidity Sensor Data to IO.adafruit

13

Project 3 - Controlling Devices through Internet

14

Project 4 - Using Triggers to Automate Actions

15

Project 5 - Using Google Voice to control devices IO.adafruit

16

Bonus Lectures on SSD1306 - A OLED Display

17

Bonus 2

About this course

The Fastest way to Prototype IOT Products/Applications Using NodeMCU(Powered by ESP8266) + MicroPython + PyCharm

Requirements

  • Little Knowledge on Basic Electronics
  • A Bread Board with a bunch of jumper wires and supply MB102(Optional) (Costs 4$)
  • ESP8266 NodeMCU-V3 Board(Costs 3$, where as a PyBoard costs you 10 times)
  • RGB LED(Costs 0.5$)
  • Motion Sensor SW420 (Costs 0.75$)
  • Temperature and Humidity Sensor DHT11(Costs:1$)
  • PyCharm(Free)
  • Urge to Complete Course
  • [For Bonus Lectures] 128 x 64 OLED Display - SSD1306 (Costs 1$)
  • [For Bonus Lectures] uLiDAR Moule - VL6180x (Costs 3$)

Description

Updates: 

UPDATE 1 : After listening to candidates expressing their discomfort with instructor's accent ,Captions(CC) of all Lectures in the course are properly transcribed now and are not automatic(annoying)

UPDATE 2 : After Request from Students Asking about interfacing a display, we have uploaded few bonus lectures on working with SSD1306, a 128 x 64 OLED display, after taking these labs you will be able to draw objects, display your own images and run gif images over SSD1306

UPDATE 3: Using LiDAR for IOT Apps, A lecture on Gesture recognition using VL6180x is added to bonus lectures, vl6180x from STMicroElectronics is a popular sensor for mobile phones, which can also be used for IOT Apps, Have a look for new Ideas

Description :

This course gives a brief introduction to IOT and enables the students/enthusiasts to create very easy and useful applications through NodeMCU hardware and supporting sensors in a fastest way.

Regular courses which teach IOT through Raspberry pi may incur a cost of 30 - 50 $ including different sensors to complete the learning process, where as this course uses hardware like NodeMCU which is Open-source, Interactive, Low cost, Simple, Smart and WI-FI enabled hardware powered by ESP8266

Regular courses use C/ C++ language to code,Where as this course emphasizes more on the use of MicroPython which is a lean and efficient implementation of the Python 3 programming language that includes a small subset of the Python standard library and is optimised to run on microcontrollers and in constrained environments.

This Course uses popular PyCharm IDE from Jetbrains available free as community edition 

Course is completely experimental / lab based and has no boring lectures

It shows how to interface and grab data from sensors like Vibration, Temperature, Humidity, Pressure

It teaches how to post / visualize the data grabbed from sensor on to internet, visualization brokers/interfaces like Thingspeak and Adafruit.IO are used 

Apart from visualization the course also teaches how to control IOs/devices connected to NodeMCU hardware through internet from any place in the world using Google Voice Assistant and If This Then That (IFTTT) platforms

Our rationale to build/teach this course: We went through different courses on IOT and found that there is need for a course which can teach people about building IOT Apps under limited budget


Who this course is for:

  • Hobbyists, Electronics Beginner, Electronics Professionals

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