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IT & SoftwareOther IT & SoftwareInternet Of Things

IoT Data Analytics

Practical introduction to Internet of Things (IoT), Data Analytics, NodeMCU, ESP8266 and Machine Learning,Learn by doing
Rating: 4.3 out of 54.3 (25 ratings)
99 students
Created by Bapuji Kanaparthi
Last updated 10/2021
English

What you'll learn

  • Quick start Building IoT Projects
  • Design IoT Devices using Thingspeak Platform, NodeMCU (ESP8266)
  • Data Collection using IoT Devices
  • MATLAB
  • Data Analysis and Data Visualization
  • Machine Learning

Requirements

  • Computer fundamentals, Programming fundamentals,
  • You don't need to have prior knowledge on IOT or Data Analytics or MATLAB

Description

Welcome to IoT Data Analytics Course. This is practical course to learn IoT and Data Analytics from the beginning. Learn how to program NOdeMCU (ESP8266), collecting data and data analysis.

There are billions of devices in homes, industries, cities, hospitals, cars, and thousands of other places. With the rapid increase of devices, you increasingly need solutions to connect them, and collect, store, and analyze device data. Data in its raw form is not always useful. Data need to be processed to transform into information.

In this course, you will learn how to collect and analyse sensor data.  You will learn, data processing, data visualization and machine learning algorithms for predictive analytics.

The following are the various topics covered in this training:

  • Introduction to Internet of Things (IoT)

  • Getting started with Arduino Programming

  • Learn to work with NodeMCU (ESP8266  based IoT Board)

  • Collecting Data from sensors locally

  • Sending Sensor Data to IoT Cloud (Thingspeak)

  • Introduction to MATLAB

  • Data Analysis

  • Data Visualization

  • Machine Learning

You'll get to practice the skills learned during the training, by doing more than five projects on Internet of Things (IoT) and Data analytics.

Hands on Projects

  1. Sending Light Sensor Values to IoT Cloud

  2. Sending Temperature and Humidity Values to IoT Cloud

  3. Sensor Data Visualization

  4. Energy savings with Anomaly Detection using Z-Score Analysis

  5. Correlation between Temperature and Humidity and Regression

  6. Temperature Prediction using Polynomial Regression

What am I going to get from this course?

  • Build IoT projects for sensor data collection

  • Apply the fundamentals of machine learning and statistics to extract value from IoT data

  • Understand different business use-cases for IoT data


Who this course is for:

  • Engineers who would like to understand the methods used to analyze IoT data in large scale
  • Executives who would like to understand how to utilize IoT data to create business value
  • Engineering Graduates , IoT Develpers, Data Scientists

Instructor

Bapuji Kanaparthi
Founder at Appleton Innovations
Bapuji Kanaparthi
  • 4.3 Instructor Rating
  • 25 Reviews
  • 99 Students
  • 1 Course

Received Master of Technology from Indian Institute of Technology (IIT) Bombay . Served as project head, project leader and Assistant professor for more than 7 years. With several years of experience as a Passionate Developer and Engineer, I am now an Founder at Appleton Innovations.

I am having 10+ years’ experience in Internet of Things Research and Training. Designed and developed Internet of Things Boards and kits with trademark “HUEBITS”

Trained more than 5000 students on Internet of Things (IoT) and Machine Learning (ML)

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