Internet of Things

Course Code: 0110

$999

Overview
Schedule classes
What you'll learn
Outline
Prerequisites
Who should attend
Certification

Overview

The Internet of Things course offered by Cognixia introduces participants to advanced IoT concepts, methodologies, and protocols used for communication. This includes next-generation, IoT-friendly applications, physical-layer protocols, and widely accepted IoT frameworks and standards. The program covers popular, service-rich cloud platforms and focuses on how to build and deploy IoT solutions. Practical use-cases and case studies are included to ensure that the participant develops an ability to work through real-life scenarios.

Schedule Classes

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Course Delivery

This course is available in the following formats:

Live Classroom
Duration: 16 days

Live Virtual Classroom
Duration: 16 days

*shipping charges extra

What You'll learn

IoT technology and tools
Core concepts and background technologies
Features of the IoT landscape
Sensors, microcontrollers and communication interfaces to design and build IoT devices
Designing and building a network based on the client server
Publishing/subscribing to connect, collect data, monitor and manage assets
Writing device, gateway and server-side scripts and apps, enabling them to aggregate and analyze sensor data
Selecting application-layer protocols and web services architectures for a seamless integration of various components within an IoT ecosystem
Reviewing standard development initiatives and reference architectures
Deploying various types of analytics on machine data to define context, find faults, ensure quality and extract valuable actionable insights
Cloud infrastructure, services, APIs and architectures of commercial and industrial cloud platforms
Prevalent computing architectures, including distributed, centralized, and edge/fog computing

Outline

Module 1: Concept and definitions

Embedded Systems
Computer Networks
M2M (Machine to Machine Communication)
Internet of Everything (IoE)
Machine Learning
Distributed Computing
Artificial Intelligence
Industrial Automation
Interoperability, Identification, Localization, Communication
Software Defined Assets

Module 2: Understanding IT and OT Convergence: Evolution of IIoT & Industry 4.0

Module 3: IoT Adoption

Market statistics
Early adopters
Roadmap

Module 4: Business opportunities: Product + Service model

Development
Deployment and monetization of applications as service

Module 5: Use cases

Module 6: Concept of Data, Information, Knowledge and Wisdom

Knowledge discovery process
DIKW pyramid and relevance to IoT
Microcontrollers: Cost, performance and power consumption
Commercial microcontroller-based development boards
Selection criteria and trade-offs
Industrial networks, M2M networks

Module 7: Sensor Data Mining and Analytics

Transducer: Sensor and Actuator
Types of sensors
Sampling
Analog to digital conversion
Selection criteria of sensor and ADC
Data acquisition, storage and analytics
Signals and systems
Signal processing, systems classification, sampling theorem
Ensuring quality and consistency of data
Real-time analytics
Understanding fundamental nuances of IoT and Big Data
Usage of IoT data in various business domains to gain operational efficiency
Edge analytics
Data aggregation on edge gateway

Module 8: Wireless Sensor Area Networks (WSAN): Evolution of M2M and IoT Networks and Technologies

Sensor nodes
Sensor node architecture
WSN/M2M communication technologies
Bluetooth, Zigbee and WiFi communication technologies
Cellular communication and LPWAN (LoRa and LoRaWAN) technologies
Topologies
Applications

Module 9: Design and development of IoT systems

IoT reference architectures
Standardization initiatives
Interoperability issues
IoT design considerations
Architectures device, network and cloud
Centralized vs distributed architectures
Networks, communication technologies and protocols
Smart asset management: Connectivity, visibility, analytics, alerts

Module 10: Cloud computing and platforms

Public, private and hybrid cloud platforms and deployment strategy
Industrial Gateways
Commercial gateways solutions from various vendors
Cloud-based gateway solutions
IaaS, SaaS, PaaS models
Cloud components and services
Device management
Databases, visualization
Reporting
Notification/alarm management
Security management
Cloud resource monitoring and management
Example platforms: ThingSpeak, Pubnub, AWS IoT
AWS IoT Services – Device registry, Authentication and authorization, Device gateway, Rules engine, Device shadow

Module 11: IoT Security

Standards and best practices
Common vulnerabilities
Attack surfaces
Hardware and software solutions
Open-source initiatives

Module 12: Analytics

Descriptive, diagnostic, predictive, and prescriptive
Analytics using Python advance packages: NumPy, SciPy, Matplotlib, Pandas and Sci-kit learn
Case studies and roadmap
Cold chain monitoring
Asset tracking using RFID and GPRS/GPS

Module 13: Hands-on/Practical Exercises

Programming micro-controllers (Arduino, NodeMCU)
Building HTTP and MQTT based M2M networks
Interfacing Analog and Digital sensors with microcontrollers for real-time data acquisition, as well as storage and analysis on IoT endpoints and edges
Developing microcontroller-based applications to understand event-based, real-time processing and in-memory computations
Setting up Raspberry Pi as gateway to aggregate data from thin clients
Python programming on Raspberry Pi to analyze collected data
GPIO programming using Python and remote monitoring /control
Pushing collected data to cloud platforms
Uploading data on local gateway as cache
Uploading data on cloud platforms
Monitoring and controlling devices using android user apps and Bluetooth interfaces
Building wireless sensor networks using WiFi
Remote controlling machines using cloud based apps
Remote controlling machines using device based apps through cloud as an intermediate node
Interfacing Raspberry Pi with AWS IoT Gateway service to exchange messages
Data cleaning, sub-setting and visualization
Set of Python exercises to demonstrate descriptive and predictive analytics

Module 14:Hardware Kit

1. Development Boards

Raspberry Pi 3
Arduino Mega (ATMega2560) with USB cable
ESP8266 NodeMcu

2. Electronic Components

Sensors – Analog temperature sensor (LM35)
IR Proximity Sensor
Switches – Push Button (10)
Breadboard
LEDs (10)
Resistors (10)
Connecting leads (25)
Memory Card (16 GB)
HDMI – VGA Converter
1A Power Adapter

3. Communication Modules

WiFi – ESP01
Bluetooth – HC05

Prerequisites

Cognixia’s Internet of Things course is designed for professionals with a basic understanding of electronic circuit design, microcontrollers, and programming languages, as well as knowledge of computer fundamentals.

Who Should Attend

Cognixia’s Internet of Things course is highly recommended for current and aspiring –

IT professionals
Electrical and electronics engineers
Designers
Solution architects
Existing and budding entrepreneurs keen to build smart solutions for customers
Fresh graduates who meet the prerequisite criteria

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Certification

Participants will be awarded with an exclusive certificate upon successful completion of the program. Every learner is evaluated based on their attendance in the sessions, their scores in the course assessments, projects, etc. The certificate is recognized by organizations all over the world and lends huge credibility to your resume.