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Azure Data Scientist Associate Certification Guide

You're reading from   Azure Data Scientist Associate Certification Guide A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam

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Product type Paperback
Published in Dec 2021
Publisher Packt
ISBN-13 9781800565005
Length 448 pages
Edition 1st Edition
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Authors (2):
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Andreas Botsikas Andreas Botsikas
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Andreas Botsikas
Michael Hlobil Michael Hlobil
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Michael Hlobil
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Starting your cloud-based data science journey
2. Chapter 1: An Overview of Modern Data Science FREE CHAPTER 3. Chapter 2: Deploying Azure Machine Learning Workspace Resources 4. Chapter 3: Azure Machine Learning Studio Components 5. Chapter 4: Configuring the Workspace 6. Section 2: No code data science experimentation
7. Chapter 5: Letting the Machines Do the Model Training 8. Chapter 6: Visual Model Training and Publishing 9. Section 3: Advanced data science tooling and capabilities
10. Chapter 7: The AzureML Python SDK 11. Chapter 8: Experimenting with Python Code 12. Chapter 9: Optimizing the ML Model 13. Chapter 10: Understanding Model Results 14. Chapter 11: Working with Pipelines 15. Chapter 12: Operationalizing Models with Code 16. Other Books You May Enjoy

Questions

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

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