IL - Designing and Implementing IoT Solutions

Course Overview
This course provides a comprehensive introduction to designing and implement Internet of Things (IoT) solutions on Microsoft Azure. The course covers both directions of message flow from device-to-cloud and cloud-to device, building analytics solutions atop the real-time telemetry, managing devices and securing the solution.
Course Details
  • Duration: 3 Days
  • Level: 300
Who this course is designed for
  • Developers

Course Objectives

What You Will Learn
  • Understand the key capabilities of Azure IoT Suite
  • Understand the core messaging services provided by IoT Hub and Event Hubs
  • Understand core processing services including HDInsight, Stream Analytics and SQL Data Warehouse
  • Understand common architectures including Lambda architectures
  • Understand how to manage and secure the IoT solution

Course Modules

Module 1: Overview of the Azure IoT Platform
In this module, students will learn the basics of IoT terminology and where the Microsoft Azure services fit. This module introduces the Lambda Architecture, which is used as a reference architecture for building an analytics data pipeline that processes telemetry data from devices and makes it available to alerting, management and reporting applications. It also introduces the two messaging flows of any IoT solution: device-to-cloud and cloud-to-device. Finally, the key services IoT Hub and IoT Suite are introduced.;
Module 2: Azure Certified for IoT Devices & Platforms
In this module, students will be introduced to the devices and platforms that work well with Azure IoT services. Students will get implement a simple device that produces telemetry for analysis and is available for cloud initiated management. ;
Module 3: Gateways
In this module, students will be introduced to the concepts behind field gateways that are responsible for performing message processing on-premises, between the IoT device and the cloud. This module will demonstrate the use the Azure IoT Gateway SDK to implement custom gateways. ;
Module 4: Real-Time Ingest & Storage
In this module, students will learn about the protocols for real-time ingest including HTTP, AMQP and MQTT and the storage of data received using queue based services provided by IoT Hub and Event Hubs. ;
Module 5: Real-time Processing
In this module, the student will learn about different services and capabilities of Azure for processing ingested real-time data. Key concepts such as tuple-at-time and micro-batch processing are introduced. Services covered include HDInsight with Apache Storm, HDInsight with Storm/Trident, HDInsight with Spark Streaming, Web Jobs, Azure Functions, and Stream Analytics.;
Module 6: Command and Control
This module will help the student understand the cloud-to-device flow of messaging, where services running in Azure are able to issue command to specific devices using IoT Hub, including how to use Azure IoT Hub device management services.;
Module 7: Intelligence & Machine Learning
In this module, student will understand the fundamentals of machine learning using Azure Machine Learning. Covered topics include ML Studio, Training Experiments, Predictive Experiments, operationalizing experiments with Web Services and Cortana Intelligence components.;
Module 8: Device Management & Security
In this concluding module, the student will look horizontally across the data pipeline to understand how to manage device access and secure the IoT solution.;

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