Book Image

Azure Data Scientist Associate Certification Guide

By : Andreas Botsikas, Michael Hlobil
Book Image

Azure Data Scientist Associate Certification Guide

By: Andreas Botsikas, Michael Hlobil

Overview of this book

The Azure Data Scientist Associate Certification Guide helps you acquire practical knowledge for machine learning experimentation on Azure. It covers everything you need to pass the DP-100 exam and become a certified Azure Data Scientist Associate. Starting with an introduction to data science, you'll learn the terminology that will be used throughout the book and then move on to the Azure Machine Learning (Azure ML) workspace. You'll discover the studio interface and manage various components, such as data stores and compute clusters. Next, the book focuses on no-code and low-code experimentation, and shows you how to use the Automated ML wizard to locate and deploy optimal models for your dataset. You'll also learn how to run end-to-end data science experiments using the designer provided in Azure ML Studio. You'll then explore the Azure ML Software Development Kit (SDK) for Python and advance to creating experiments and publishing models using code. The book also guides you in optimizing your model's hyperparameters using Hyperdrive before demonstrating how to use responsible AI tools to interpret and debug your models. Once you have a trained model, you'll learn to operationalize it for batch or real-time inferences and monitor it in production. By the end of this Azure certification study guide, you'll have gained the knowledge and the practical skills required to pass the DP-100 exam.
Table of Contents (17 chapters)
Section 1: Starting your cloud-based data science journey
Section 2: No code data science experimentation
Section 3: Advanced data science tooling and capabilities

Technical requirements

To provision an Azure ML workspace, you will need an Azure subscription. You can get a free trial by visiting If you want to use an existing subscription, you will need to request the owner of the subscription to provide you with the following Resource Group items:

  • packt-azureml-rg
  • packt-azureml-cli-rg

This book assumes that you have either a Contributor role or an Owner role on these resource groups. You are going to deploy an Azure ML workspace in both of those resource groups: one through the Azure portal and one through the Azure CLI.

Azure ML requires the following providers to be registered in the Azure subscription that hosts the resource groups you are planning to use:

  • Microsoft.MachineLearningServices
  • Microsoft.KeyVault
  • Microsoft.Storage
  • Microsoft.insights
  • Microsoft.ContainerRegistry
  • Microsoft.Notebooks

If you are the Owner of the subscription, Azure will automatically...