Azure Data Scientist Associate Certification Guide

By Andreas Botsikas , Michael Hlobil
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About this book

This book 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.

The book starts with an introduction to data science. In that section, you will learn the terminology used throughout the book. You then move into the Azure Machine Learning (AzureML) workspace, your working area for the rest of the book. You will discover the studio interface and manage the various components, like the data stores and the compute clusters.

You will then focus on no-code, low-code experimentation. You will discover the Automated ML wizard to locate and deploy optimal models for your dataset. You will also learn how to run end-to-end data science experiments using the designer provided in AzureML studio.

You will then explore the AzureML Software Development Kit (SDK) for Python. You will create experiments and publish models using code. You will learn how to optimize your model's hyperparameters using Hyperdrive. Then you will learn how to use responsible AI tools to interpret and debug your models. Once you have a trained model, you will learn to operationalize it for batch or real-time inferences and how you can monitor it in production.

With this knowledge, you will clear the DP100 exam with flying colours.

Publication date:
December 2021

About the Authors

  • Andreas Botsikas

    Andreas Botsikas is an experienced advisor with a demonstrated history of working in the computer software industry. He is skilled in Computer Science and Data Science and is a strong engineering professional with a “Doctor of Philosophy” (Ph.D.) in Optimization on the use of industrial resources via artificial intelligence from National Technical University of Athens.

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  • Michael Hlobil

    Michael is an experienced architect focused on quickly understanding customer’s 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 is a visiting lecturer in the University of Vienna, Technical University of Vienna for Integration and BPI. He has published various journals/papers on EDIFACT, Integration and BPI.

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Azure Data Scientist Associate Certification Guide
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