Data, Analytics & AI Category Banner Image

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

Length 1 day
Price NZD 995 exc GST

Course overview

View dates &
book now

Course locations >>

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.

Request Course Information

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

Microsoft Azure at Lumify Work

Lumify Work has been delivering effective training across all Microsoft products for over 30 years. We are proud to be both Australia's and New Zealand’s first Microsoft Gold Learning Solutions Partner and the winner of the Microsoft MCT Superstars Award for FY24, which formally recognises us as having the highest quality Microsoft Certified Trainers (MCTs) in ANZ. All Lumify Work Microsoft Azure courses follow Microsoft Official Curriculum (MOC) and are led by MCTs.

View all Microsoft Azure courses

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

Prerequisites

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.