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Matt Milner, Xavier Morera, Tim Warner, Jared Rhodes, Neeraj Kumar, and Saravanan Dhandapani

Microsoft Azure contains a massive offering of services that can be used together to implement the data science workflow. This path walks you through this workflow, as it is implemented in Microsoft Azure.

What You'll Learn

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Microsoft Azure contains a massive offering of services that can be used together to implement the data science workflow. This path walks you through this workflow, as it is implemented in Microsoft Azure.

What You'll Learn

  • Source, clean, and prepare data using Microsoft Azure
  • Implement feature selection using Microsoft Azure
  • Build models and evaluate their effectiveness in Microsoft Azure
  • Use Microsoft Azure services to deploy and manage your model
  • Communicate results to the business using the Microsoft Azure platform
  • Enroll now

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    What's inside

    Seven courses

    Sourcing Data in Microsoft Azure

    (1 hours)
    This course targets software developers looking to source data from inside and outside of the cloud. You'll learn foundational knowledge of data types, data policy, and finding data.

    Cleaning and Preparing Data in Microsoft Azure

    (1 hours)
    This course targets software developers and data scientists looking to understand the initial steps in a machine learning solution. The content will showcase methods and tools available using Microsoft Azure.

    Exploring Data in Microsoft Azure Using Kusto Query Language and Azure Data Explorer

    (2 hours)
    You will learn about Azure's data exploration service and its integration with other services for end-to-end data analytics. This course will provide you with the skills and confidence to be a data scientist.

    Feature Selection and Extraction in Microsoft Azure

    (1 hours)
    One of the most important aspects of Machine Learning is using the right data for your models. In this course, you will learn how to extract, normalize, and select the best features for your models using Azure Machine Learning Studio.

    Developing Models in Microsoft Azure

    (1 hours)
    It's common to spend a lot of resources on identifying an optimal machine learning model. This course will teach you how to simplify this process using various cutting edge features offered by Microsoft Azure Machine Learning service.

    Evaluating Model Effectiveness in Microsoft Azure

    (0 hours)
    This course is for data science practitioners who use Azure Machine Learning Service and want to improve their ML model accuracy, efficiency, and explainability.

    Deploying and Managing Models in Microsoft Azure

    (0 hours)
    In this course, you'll learn how to manage the life cycle of models using tools in Microsoft Azure.

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