Overview
IoT is undoubtedly revolutionizing industrial, economic and social landscapes. Experts predict that there will be more than 50 billion connected devices by 2020. IoT cloud platforms play a pivotal role in efficient provisioning and management of connected devices. Microsoft Azure offers an optimized collection of ready-to-deploy services and solutions to rapidly build end-to-end IoT solutions.
Learn the fundamentals of Microsoft Azure, under the guidance of our experienced trainers. With this course, you would start out with device basics, like registration and tracking, and then move on implementing cloud-to-device and device-to-cloud messaging. This course help you gain an experience of Azure analytics to perform real-time monitoring of incoming data and to generate alerts, store sensor data on the cloud using DocumentDB, implement basic Power BI features, and add remote management and update capabilities to your device. You would also learn about deploying analytics at Edge using IoT Edge SDK from Azure. The course includes hands-on learning using open source starter kit based on Raspberry Pi.
Curriculum
- 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
- OT Components: Industrial control system, PLC, SCADA, DCS
- IT Components: Hardware, Software, People ,Processes
- IoT Adoption
- Market statistics, Early adopters, Roadmap
- Business opportunities: Product + Service model
- Development, deployment and monetization of applications as service
- Use cases
- Knowledge discovery process
- DIKW pyramid and relevance with IoT
- IoT prototyping
- Microcontrollers: cost, performance, and power consumption
- Commercial microcontroller based development boards
- Selection criteria and tradeoffs
- Understanding IoT data value chain
- Building an organization-wide data analytics strategy
- Transducer: Sensor and Actuator
- Sensors – Types of sensors, sampling, analog to digital conversion, selection criteria of sensor and ADC
- Data acquisition, storage and analytics
- 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
Prerequisites
FAQs
