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

Class Dates
(click date for class times)
(click Enroll for locations)
4/25
Class Dates and Times
04/25/2025Friday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
Last Reg Date4/22
 
5/23
Class Dates and Times
05/23/2025Friday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
 
6/20
Class Dates and Times
06/20/2025Friday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
 
7/18
Class Dates and Times
07/18/2025Friday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
 
8/15
Class Dates and Times
08/15/2025Friday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
 
9/12
Class Dates and Times
09/12/2025Friday 10:00-4:45 EDT
  9:00-3:45 CDT
  8:00-2:45 MDT
  7:00-1:45 PDT
 
Fee:  $595

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

 

Overview

The DP-3007: Train and Deploy a Machine Learning Model with Azure Machine Learning course covers the end-to-end process of building, training, and
deploying machine learning models using Azure Machine Learning, including data preparation, model training, and deployment strategies.

Objectives

• 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

Target Audience

• Data Scientist
• AI Engineer

COURSE OUTLINE

Make data available in Azure Machine Learning

  • • Access data by using Uniform Resource Identifiers URIs
  • • Connect to cloud data sources with datastores
  • • Use data asset to access specific files or folders
  • • Lab Make data available in Azure Machine Learning

Work with compute targets in Azure Machine Learning

  • • Choose the appropriate compute target
  • • Work with compute instances and clusters
  • • Manage installed packages with environments
  • • Lab Work with compute resources

Work with environments in Azure Machine Learning

  • • Understand environments in Azure Machine Learning
  • • Explore and use curated environments
  • • Create and use custom environments
  • • Lab Work with environments

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

  • • Convert a notebook to a script
  • • Test scripts in a terminal
  • • Run a script as a command job
  • • Use parameters in a command job
  • • Lab Run a training script as a command job

Track model training with MLflow in jobs

  • • Use MLflow when you run a script as a job
  • • Review metrics parameters artifacts and models from a run
  • • Lab Use MLflow to track training jobs

Register an MLflow model in Azure Machine Learning

  • • Log models with MLflow
  • • Understand the MLmodel format
  • • Register an MLflow model in Azure Machine Learning
  • • Lab Log and register models with MLflow

Deploy a model to a managed online endpoint

  • • 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
  • • Lab Deploy an MLflow model to an online endpoint

 

View outline in Word

ADP3A7

Attend hands-on, instructor-led DP-3007: Train and Deploy a Machine Learning Model with Azure Machine Learning training classes at ONLC's nationwide locations. Not near one of our locations? Attend these same live classes from your home/office PC via our Remote Classroom Instruction (RCI) technology.

For additional training options, check out our list of Courses and select the one that's right for you.

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