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


In each chapter, you will find a couple of questions so that you can test your knowledge regarding what was covered in this chapter:

  1. How many data scientists can work on a single compute instance that has 8 cores and 56 GB of RAM?

    a. Only one.

    b. Up to two.

    c. Up to five.

    d. As many as they want, as long as they don't deplete the compute resources.

  2. What type of credentials do you need to provide to access a data lake store that's either Gen 1 or Gen 2?

    a. A Personal Access Token (PAT)

    b. A service principal's client ID and secret

    c. Your own AAD user credentials

    d. No credentials are needed

  3. Which of the following Azure tools can help you orchestrate data moving from an on-premises environment?

    a. Blob storage

    b. Azure Active Directory

    c. Azure Data Factory

    d. Azure ML workspace