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Microsoft

Become a Machine Learning Engineer for Microsoft Azure

Microsoft via Udacity Nanodegree

Overview

In this program, students will enhance their skills by building and deploying sophisticated machine learning solutions using popular open source tools and frameworks, and gain practical experience running complex machine learning tasks using the built-in Azure labs accessible inside the Udacity classroom.

Syllabus

Prerequisite Knowledge

Prior experience with Python, Machine Learning, and StatisticsSee detailed requirements.

  • Using Azure Machine Learning

    Machine learning is a critical business operation for many organizations. Learn how to configure machine learning pipelines in Azure, identify use cases for Automated Machine Learning, and use the Azure ML SDK to design, create, and manage machine learning pipelines in Azure.

    Optimizing an ML Pipeline In Azure  
  • Machine Learning Operations

    This course covers a lot of the key concepts of operationalizing machine learning, from selecting the appropriate targets for deploying models, to enabling Application Insights, identifying problems in logs, and harnessing the power of Azure’s Pipelines. All these concepts are part of core DevOps pillars that will allow you to demonstrate solid skills for shipping machine learning models into production.

    Operationalizing Machine Learning  
  • Capstone Project

    The program capstone gives you the opportunity to use the knowledge you have obtained from this Nanodegree program to solve an interesting problem. You will have to use Azure’s Automated ML and HyperDrive to solve a task. Finally, you will have to deploy the model as a webservice and test the model endpoint.

    Training and Deploying a Machine Learning Model in Azure  

Taught by

Noah Gift, Alfredo Deza, Erick Galinkin and Soham Chatterjee

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