his course helps you to understand about the fundamentals required to build an IoT product and provides a detailed learning on embedded systems and cloud computing. The focus of this course is to help you understand and apply IoT concepts practically. All the necessary software, hardware, platform, protocols are covered across the modules wherever it is required.
Upon successful completion of the course, the learner will be able to
Understand what is an IoT thing, IoT Ecosystem, big picture, Use cases, layers and communication protocols
Learn how to work with Arduino UNO, Arduino Nano, Sensors, Displays, Keypads, Relays, Power converters the whole nine yards.
Learn how to connect your IoT devices to the internet over Ethernet or Wifi.
Learn how to work with Ethernet Shield, Wifi chip ESP8266 and Development kit like NodeMCU.
Understand software ecosystem, working with the Arduino IDE.
Learn how to write code (sketch) for your devices from basics.
Understand the different options to Connect your device to an IoT Cloud platform, DB's.
Learning through E-Box is completely Hands-on and practice based thereby helping you understand the intricacies of Live Project Scenarios
E-Box’s programs and Courses are designed by Professionals in the Industry & Academicians, assuring a quality learning experience
With 100’s Mentors online ready to get your Doubts clarified and to Hand Hold you, you will always have someone to sort things our for you
All our Mentors are Top Professionals from their respective Industries. In E-Box you Learn and get mentored by professionals
Auto Evaluation is the Core of E-Box. Your solutions and answers are evaluated instantaneously by E-Box, thereby saving learners a lot of time
With Auto - Evaluation being the core of the Platform, E-Box uses AI & ML to assist Learners during their course of Study
E-Box’s AI algorithms provide you with Exercises that are Personalised and Adaptive based on your Interest and Calibre
Data becomes the core for evolving a personalised learning. E-Box uses these metrics for an Auto Corrective Learning Process