Machine Learning Operations (MLOps) - Microsoft Cloud Workshop (40559)

40559: Microsoft Cloud Workshop: MLOps Certification Training Course Overview

40559: Microsoft Cloud Workshop: MLOps training course is designed to learn how Trey Research can leverage Deep Learning technologies to scan through their vehicle specification documents to find compliance issues with new regulations, and manage the classification through their web application. In this training class, you will learn model creation, application packaging, model deployment and application deployment needs to occur as one unified repeatable, pipeline.

Target Audience:

This course is recommended 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.

Machine Learning Operations (MLOps) - Microsoft Cloud Workshop (40559) (Duration : 8 Hours) Download Course Contents

Live Virtual Classroom
Group Training 550
02 Aug 09:00 AM - 05:00 PM CST
(8 Hours/Day)
06 Sep 09:00 AM - 05:00 PM CST
(8 Hours/Day)
1-on-1 Training (GTR) 600
4 Hours
8 Hours
Week Days
Week End

Start Time : At any time

12 AM
12 PM

GTR=Guaranteed to Run
Classroom Training (Available: London, Dubai, India, Sydney, Vancouver)
Duration : On Request
Fee : On Request
On Request
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Course Modules

Module 1: Whiteboard Design Session – MLOps
  • Review the customer case study
  • Design a proof of concept solution
  • Present the solution
Module 2: Hands-on lab – MLOps
  • Creating and evaluating compliance classification models
  • Registering the model
  • Setup New Project in Azure DevOps
  • Setup and Run the Build Pipeline
  • Setup the Release Pipeline
  • Test Build and Release Pipelines
  • Testing the deployed solution
  • Examining deployed model performance
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Course Prerequisites
  • Basic Computer Knowledge.
  • Review the customer case study
  • Design a proof of concept solution
  • Present the solution
  • Creating and evaluating compliance classification models
  • Registering the model
  • Setup New Project in Azure DevOps
  • Setup and Run the Build Pipeline
  • Setup the Release Pipeline
  • Test Build and Release Pipelines
  • Testing the deployed solution
  • Examining deployed model performance

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