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You're reading from  Azure Data Scientist Associate Certification Guide

Product typeBook
Published inDec 2021
Reading LevelBeginner
PublisherPackt
ISBN-139781800565005
Edition1st Edition
Languages
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Authors (2):
Andreas Botsikas
Andreas Botsikas
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Andreas Botsikas

Andreas Botsikas is an experienced advisor working in the software industry. He has worked in the finance sector, leading highly efficient DevOps teams, and architecting and building high-volume transactional systems. He then traveled the world, building AI-infused solutions with a group of engineers and data scientists. Currently, he works as a trusted advisor for customers onboarding into Azure, de-risking and accelerating their cloud journey. He is a strong engineering professional with a Doctor of Philosophy (Ph.D.) in resource optimization with artificial intelligence from the National Technical University of Athens.
Read more about Andreas Botsikas

Michael Hlobil
Michael Hlobil
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Michael Hlobil

Michael Hlobil is an experienced architect focused on quickly understanding customers' business needs, with over 25 years of experience in IT pitfalls and successful projects, and is dedicated to creating solutions based on the Microsoft Platform. He has an MBA in Computer Science and Economics (from the Technical University and the University of Vienna) and an MSc (from the ESBA) in Systemic Coaching. He was working on advanced analytics projects in the last decade, including massive parallel systems and Machine Learning systems. He enjoys working with customers and supporting the journey to the cloud.
Read more about Michael Hlobil

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Section 1: Starting your cloud-based data science journey

An Azure Data Scientist Associate is a subject matter expert with applied data science and machine learning knowledge, able to run machine learning workloads on Azure. The responsibilities for this role include planning and creating a suitable working environment for data science workloads on Azure. In this section, you will get an overview of the data science and machine learning terminology used throughout the book. You will also learn how to provision and configure the Azure Machine Learning services, the de facto environment for running machine learning experiments in the Azure cloud.

This section comprises of the following chapters:

  • Chapter 1, An Overview of Modern Data Science
  • Chapter 2, Deploying Azure Machine Learning Workspace Resources
  • Chapter 3, Azure Machine Learning Studio Components
  • Chapter 4, Configuring the Workspace
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Published in: Dec 2021Publisher: PacktISBN-13: 9781800565005
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Authors (2)

author image
Andreas Botsikas

Andreas Botsikas is an experienced advisor working in the software industry. He has worked in the finance sector, leading highly efficient DevOps teams, and architecting and building high-volume transactional systems. He then traveled the world, building AI-infused solutions with a group of engineers and data scientists. Currently, he works as a trusted advisor for customers onboarding into Azure, de-risking and accelerating their cloud journey. He is a strong engineering professional with a Doctor of Philosophy (Ph.D.) in resource optimization with artificial intelligence from the National Technical University of Athens.
Read more about Andreas Botsikas

author image
Michael Hlobil

Michael Hlobil is an experienced architect focused on quickly understanding customers' business needs, with over 25 years of experience in IT pitfalls and successful projects, and is dedicated to creating solutions based on the Microsoft Platform. He has an MBA in Computer Science and Economics (from the Technical University and the University of Vienna) and an MSc (from the ESBA) in Systemic Coaching. He was working on advanced analytics projects in the last decade, including massive parallel systems and Machine Learning systems. He enjoys working with customers and supporting the journey to the cloud.
Read more about Michael Hlobil