Length
3 days
Version
A

Overview

Learn how to use Azure services to develop, train, and deploy, machine learning solutions.

The course starts with an overview of Azure services that support data science. From there, it focuses on using Azure’s premier data science service, Azure Machine Learning service, to automate the data science pipeline.

This course is focused on Azure and does not teach the student how to do data science. It is assumed students already know that.

Please note: Microsoft has retired Azure training from the Software Assurance Training Voucher (SATV) catalogue. From 1st February 2020 we are no longer able to accept SATVs for this course.

Key Topics

Detailed Info
  • Doing Data Science on Azure
  • Doing Data Science with AML service
  • Automate Machine Learning with AML service
  • Manage and Monitor Machine Learning Models with the AML
Skills Gained
Key Topics
Target Audience
Prerequisites

Skills Gained

After completing this course, students will be able to:

  • Know how Azure services can support and augment the data science process
  • Use Azure Machine Learning service to automate the data science process end to end
  • Know about the machine learning pipeline and how the Azure Machine Learning service’s AutoML and HyperDrive can automate some of the laborious parts of it
  • Automatically manage and monitor machine learning models in the Azure Machine Learning service

Key Topics

Module 1: Doing Data Science on Azure
The student will learn about the data science process and the role of the data scientist. This is then applied to understand how Azure services can support and augment the data science process.

Lessons

  • Introduce the Data Science Process
  • Overview of Azure Data Science Options
  • Introduce Azure Notebooks

 

Module 2: Doing Data Science with Azure Machine Learning service
The student will learn how to use Azure Machine Learning service to automate the data science process end to end.

Lessons

  • Introduce Azure Machine Learning (AML) service
  • Register and deploy ML models with AML service

 

Module 3: Automate Machine Learning with Azure Machine Learning service
In this module, the student will learn about the machine learning pipeline and how the Azure Machine Learning service’s AutoML and HyperDrive can automate some of the laborious parts of it.

Lessons

  • Automate Machine Learning Model Selection
  • Automate Hyperparameter Tuning with HyperDrive

 

Module 4: Manage and Monitor Machine Learning Models with the Azure Machine Learning service
In this module, the student will learn how to automatically manage and monitor machine learning models in the Azure Machine Learning service.

Lessons

  • Manage and Monitor Machine Learning Models

Target Audience

This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models.

We can also deliver and customise this training course for larger groups – saving your organisation time, money and resources. For more information, please email us at [email protected].

Prerequisites

Before attending this course, students must have:

  • Azure Fundamentals
  • Understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one.
  • How to program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib, and seaborn.
Print course details

The supply of this course by DDLS 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.

Book Your Course

Virtual Classroom
September 28 2020 - September 30 2020
November 4 2020 - November 6 2020
January 27 2021 - January 29 2021
March 29 2021 - March 31 2021

Email Course Outline
Request a Callback

Enter your details below and we'll email you a pdf of the course outline.

Enter your details below and one of our team will give you a call to answer any questions you may have.