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Microsoft DP-3007 - Train and Deploy a Machine Learning Model with Azure Machine Learning

  • Length 1 day
Course overview
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Why study this course

To train a machine learning model with Azure Machine Learning, you need to make data available and configure the necessary compute. After training your model and tracking model metrics with MLflow, you can decide to deploy your model to an online endpoint for real-time predictions. Throughout this one-day course, you explore how to set up your Azure Machine Learning workspace, after which you train and deploy a machine learning model.

This one-day course prepares you for an Applied Skills credential.
For more than 30 years, Microsoft's industry-recognised certifications have provided proof of world-class technical proficiency for in-demand job roles. In today’s ever-changing business environment, there are also times when you need verified project-specific skills. Microsoft Applied Skills is a new verifiable credential that validates that you have the targeted skills needed to implement critical projects aligned to business goals and objectives. Applied Skills gives you a new opportunity to put your skills centre-stage, empowering you to showcase what you can do and what you can bring to key projects in your organisation.

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What you’ll learn

After completing this course, students will be able to:

  • Access data by using Uniform Resource Identifiers (URIs)

  • Connect to cloud data sources with datastores

  • Use data asset to access specific files or folders

  • Choose the appropriate compute target

  • Create and use a compute instance

  • Create and use a compute cluster

  • Understand environments in Azure Machine Learning

  • Explore and use curated environments

  • Create and use custom environments

  • Convert a notebook to a script

  • Test scripts in a terminal

  • Run a script as a command job

  • Use parameters in a command job

  • Use MLflow when you run a script as a job

  • Review metrics, parameters, artifacts, and models from a run

  • Log models with MLflow

  • Understand the MLmodel format

  • Register an MLflow model in Azure Machine Learning

  • Use managed online endpoints

  • Deploy your MLflow model to a managed online endpoint

  • Deploy a custom model to a managed online endpoint

  • Test online endpoints

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Microsoft Azure at Lumify Work

Lumify Work is your best choice for training and certification in any of Microsoft’s leading technologies and services. We’ve been delivering effective training across all Microsoft products for over 30 years, and are proud to be Australia's and New Zealand’s first and largest Microsoft Gold Learning Solutions Partner. All Lumify Work Microsoft Azure courses follow Microsoft Official Curriculum (MOC) and are led by Microsoft Certified Trainers. Join more than 5,000 students who attend our quality Microsoft courses every year.

Who is the course for?

  • AI Engineers

  • Data Engineers

  • Developers

  • Data Scientists

Course subjects

  • Make data available in Azure Machine Learning

  • Work with compute targets in Azure Machine Learning

  • Work with environments in Azure Machine Learning

  • Run a training script as a command job in Azure Machine Learning

  • Track model training with MLflow in jobs

  • Register an MLflow model in Azure Machine Learning

  • Deploy a model to a managed online endpoint


  • None

Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.

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