Exam Ref DP-100 Designing and Implementing a Data Science Solution on Azure

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  • Edition: 1st
  • Format: Paperback
  • Copyright: 2020-08-24
  • Publisher: Microsoft Press
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Supplemental Materials

What is included with this book?


Prepare for Microsoft Exam DP-100–and help demonstrate your real-world mastery of the various data science components of Microsoft Azure. Designed for IT professionals, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified Associate level. Focus on the expertise measured by these objectives:
  • Set up an Azure Machine Learning workspace 
  • Run experiments and train models 
  • Optimize and manage models 
  • Deploy and consume models 

This Microsoft Exam Ref:
  • Organizes its coverage by exam objectives
  • Features strategic, what-if scenarios to challenge you
  • Assumes you are a business user, IT professional, or student interested in cloud computing and technologies, including individuals planning to pursue more advanced Microsoft 365 certification

About the Exam 
Exam DP-100 focuses on knowledge needed to apply scientific rigor and data exploration techniques to gain actionable insights and communicate results to stakeholders; use machine learning techniques to train, evaluate, and deploy models to build AI solutions that satisfy business objectives; use applications that involve natural language processing, speech, computer vision, and predictive analytics. 

About Microsoft Certification 
Passing this exam fulfills your requirements for the Microsoft Certified: Azure Data Scientist Associate credential, demonstrating that you understand how to implement and run machine learning workloads on Microsoft Azure; in particular, using Azure Machine Learning Service.

See full details at:

Author Biography

Stefano Tucci is a Developer and Data Analytics Consultant. He is born in Italy and has a strong DB and BI background as well as a special interest in scripting languages like SQL, U-SQL, R, Python, C#, .NET, HTML, JS, and CSS. He has a Bachelor’s degree in Economics and Management and a Master’s degree in IT Security and Computer Forensics. He is currently studying for a fourth degree in Computer Engineering. He works in the IT department of an international company. Stefano is enthusiastic about technology, especially Microsoft technology. 

Table of Contents

Chapter 1
Set up an Azure Machine Learning workspace 
Create an Azure Machine Learning workspace
Manage data objects in an Azure Machine Learning workspace
Manage experiment compute contexts

Chapter 2
Run experiments and train models
Create models by using Azure Machine Learning Designer
Run training scripts in an Azure Machine Learning workspace
Generate metrics from an experiment run
Automate the model training process

Chapter 3
Optimize and manage models
Use Automated ML to create optimal models
Use Hyperdrive to rune hyperparameters
Use model explainers to interpret models
Manage models

Chapter 4
Deploy and consume models
Create production compute targets
Deploy a model as a service
Create a pipeline for batch inferencing
Publish a Designer pipeline as a web service

Rewards Program

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