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Microsoft Cloud Workshop: Predictive Maintenance for remote field devices (40560)

 

Course Overview

In this workshop, you will learn how to evaluate Microsoft's catalog of PaaS and SaaS-based IoT products to determine the optimal combination of tools to fulfill Fabrikam's needs. You will design and implement a solution that simplifies IoT device management and reporting, providing Fabrikam with a faster path to realizing their IoT strategy without requiring a lot of custom development. Next, you will learn how to deploy a trained predictive maintenance Machine Learning model and design a stream processing pipeline that makes predictions with the model in near real-time. At the end of this pipeline is an alert that is sent to the oil pump maintenance team when a pump failure is imminent.

Who should attend

This workshop is intended for Cloud Architects and IT professionals who have architectural expertise of infrastructure and solutions design in cloud technologies and want to learn more about Azure and Azure services as described in the "Summary" and "Skills gained" areas. Those attending this workshop should also be experienced in other non-Microsoft cloud technologies, meet the course prerequisites, and want to cross-train on Azure.

Prerequisites

Workshop content presumes 300-level of architectural expertise of infrastructure and solutions design. We suggest students take this prerequisite prior to attending this workshop.

  • Microsoft Azure Essentials course

Course Objectives

Design an IoT-based predictive maintenance solution in Azure.

Course Content

Module 1: Whiteboard Design Session - Predictive Maintenance for remote field devices

Lessons

  • Review the customer case study
  • Design a proof of concept solution
  • Present the solution
Module 2: Hands-on Lab - Predictive Maintenance for remote field devices

Lessons

  • Configuring IoT Central with devices and metadata
  • Run the Rod Pump Simulator
  • Creating a device set
  • Creating a useful dashboard
  • Create an Event Hub and continuously export data from IoT Central
  • Use Azure Databricks and Azure Machine Learning service to train and deploy predictive model
  • Create an Azure Function to predict pump failure
Online Training

Duration 1 day

Digital courseware

Courseware language: English

Classroom Training

Duration 1 day

Price (excl. tax)
  • Germany: 1,090.- €
  • Switzerland: CHF 840.-
  • SA Voucher: 1
    hardcoded default SA
incl. catering
Catering includes:

  • Coffee, Tea, Juice, Water, Soft drinks
  • Pastry and Sweets
  • Bread
  • Fresh fruits
  • Lunch in a nearby restaurant

* Catering information only valid for courses delivered by iTLS.


Digital courseware

Courseware language: English

 

Schedule

Instructor-led Online Training:   This computer icon in the schedule indicates that this date/time will be conducted as Instructor-Led Online Training.
Spanish
Time zone CET
Online Training Time zone: Central European Time (CET) Course language: Spanish