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

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Study for DP-100 Designing and Implementing a Data Science Solution on Azure certification exam covering machine learning models and data analytics.

Syllabus

Machine Learning Solution

<p>In this track of the DP-100: Designing and Implementing a Data Science Solution on Azure you will explore machine learning services and models.</p>

Workspaces, Data Platform Services, and Storage

<p>In this track of the DP-100: Designing and Implementing a Data Science Solution on Azure you will learn about project Jupyter and how it is used for by data scientists to perform data analysis, you will explore how to create an Azure Machine Learning workspace by creating a machine learning resources, creating compute resources, and cloning a notebook. You will also explore the differences between structured and unstructured data and explore options for storing data using Azure storage containers. You will finish this track by learning strategies for determining the best Azure Storage option based on the type of data being stored and other factors</p>

Data Stores and Deployment

<p>In this track of the DP-100: Designing and Implementing a Data Science Solution on Azure you will learn about Azure data factory as well as data stores, deployment, and model features and differential privacy.</p>

Monitoring and Optimization

<p>In this track of the DP-100: Designing and Implementing a Data Science Solution on Azure you will learn about Azure monitoring, data optimization, and high availability and disaster recovery.</p>

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