Advanced IoT Online Training

 >>  Advanced IoT Online Training

Advanced IoT Online Training


 (4.9) | 750 Ratings


Introduction


Advanced IoT Online Training Details
Track Regular Track Weekend Track Fast Track
Course Duration 30 Hrs 8 Weekends 5 Days
Hours 1hr/day 2 Hours a day 6 Hours a day
Training Mode Online Classroom Online Classroom Online Classroom
Delivery Instructor Led-Live Instructor Led-Live Instructor Led-Live


Course Curriculum

ADVANCED INTERNET OF THINGS IOT TRAINING MODULES

COURSE OBJECTIVES

  • Internet of things and its benefits in the future
  • The roles and responsibilities of an IOTA professional
  • Finding innovation
  • Major digital currency exchange programs across the globe
  • Problem formulation in IOTA
  • IOT deployment for large-scale projects
  • Designing new strategies
  • Building reports and handling the key issues associated
  • Mock sessions
  • Practice based projects
  • Career counseling

INTRODUCTION TO INTERNET OF THINGS

  • 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
  • Understanding IT and OT convergence: Evolution of IIoT & Industrie 4.0
  • IoT Adoption
  • Market statistics, Early adopters, Roadmap
  • Business opportunities: Product + Service model
  • Development, deployment and monetization of applications as service
  • Use cases

CONCEPT OF DATA, INFORMATION, KNOWLEDGE AND WISDOM

  • Knowledge discovery process
  • DIKW pyramid and relevance with IoT
  • Microcontrollers: cost, performance, and power consumption
  • Commercial microcontroller based development boards
  • Selection criteria and tradeoffs
  • Industrial networks, M2M networks

SENSOR DATA MINING AND ANALYTICS

  • Transducer: Sensor and Actuator
  • Sensors – 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 between IoT and Big data
  • Usage of IoT data in various business domains to gain operational efficiency
  • Edge analytics
  • Data Aggregation on Edge gateway

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

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

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

IOT SECURITY

  • Standards and Best practices
  • Common vulnerabilities
  • Attack surfaces
  • Hardware and Software solutions
  • Open source initiatives

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

WHAT PROJECTS ARE INCLUDED IN THIS COURSE?

The projects in IOTA training course are purely based on automation and how to implement them on large scale.

 

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Course Curriculum

ADVANCED INTERNET OF THINGS IOT TRAINING MODULES

COURSE OBJECTIVES

  • Internet of things and its benefits in the future
  • The roles and responsibilities of an IOTA professional
  • Finding innovation
  • Major digital currency exchange programs across the globe
  • Problem formulation in IOTA
  • IOT deployment for large-scale projects
  • Designing new strategies
  • Building reports and handling the key issues associated
  • Mock sessions
  • Practice based projects
  • Career counseling

INTRODUCTION TO INTERNET OF THINGS

  • 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
  • Understanding IT and OT convergence: Evolution of IIoT & Industrie 4.0
  • IoT Adoption
  • Market statistics, Early adopters, Roadmap
  • Business opportunities: Product + Service model
  • Development, deployment and monetization of applications as service
  • Use cases

CONCEPT OF DATA, INFORMATION, KNOWLEDGE AND WISDOM

  • Knowledge discovery process
  • DIKW pyramid and relevance with IoT
  • Microcontrollers: cost, performance, and power consumption
  • Commercial microcontroller based development boards
  • Selection criteria and tradeoffs
  • Industrial networks, M2M networks

SENSOR DATA MINING AND ANALYTICS

  • Transducer: Sensor and Actuator
  • Sensors – 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 between IoT and Big data
  • Usage of IoT data in various business domains to gain operational efficiency
  • Edge analytics
  • Data Aggregation on Edge gateway

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

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

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

IOT SECURITY

  • Standards and Best practices
  • Common vulnerabilities
  • Attack surfaces
  • Hardware and Software solutions
  • Open source initiatives

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

WHAT PROJECTS ARE INCLUDED IN THIS COURSE?

The projects in IOTA training course are purely based on automation and how to implement them on large scale.

 

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