40531: Microsoft Cloud Workshop: IoT and the Smart City


40531: Microsoft Cloud Workshop: IoT and the Smart City Certification Training Course Overview

40531: Microsoft Cloud Workshop: IoT and the Smart City training course is designed to learn the unique benefits of Internet of Things (IoT) to build a smart city solution to help improve traffic and public transportation in New York City. In this course, you will learn how to use a combination of the power of the cloud, along with IoT Edge devices to provide anomaly detection of city buses, engine anomalies and aggressive driving detection, location broadcasting to update bus route status, and to send traffic information to help inform the timing of traffic lights.


Microsoft exam can be taken from home.

40531: Microsoft Cloud Workshop: IoT and the Smart City Course schedule & Prices

Schedule & Prices
Course Details Schedule
Live Virtual Classroom (Instructor-Led)
Duration : 1 Day (2 Days for 4 Hours/Day)
Fee : On Request



July
8 Hours/Day
12
13
20
12-13
13-14
20-21
August
8 Hours/Day
03
09
10
17
03-04
09-10
10-11
17-18
September
8 Hours/Day
07
13
14
21
07-08
13-14
14-15
21-22
October
8 Hours/Day
05
05-06
Fly-Me-a-Trainer
Duration :
Client's Location
As per mutual convenience
Classroom Training (Available: London, Dubai, India, Sydney, Vancouver)
Duration : On Request
Fee : On Request
On Request

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Course Prerequisites
  • No formal pre-requisites for this course.

  • Learn to use IoT Hub to manage IoT devices
  • Configure and run the IoT Remote Monitoring starter solution to provision, manage, and simulate telemetry for IoT devices via IoT Hub SDKs
  • Use Azure IoT Edge to collect vehicle telemetry data, detect anomalies, and send the summarized data to Azure IoT Hub as needed
  • Create a custom endpoint in IoT Hub to route critical alerts to a Service Bus Queue
  • Create an Azure function that extracts critical alerts from the Service Bus Queue and stores them in Cosmos DB
  • Use Azure Time Series Insights to store, visualize, and query the large amounts of time series data generated by various IoT devices
  • Conduct root-cause analysis and anomaly detection