Colleagues, the Machine Learning Engineer for Microsoft Azure program will strengthen your machine learning skills and build practical experience by training, validating, and evaluating models using Azure Machine Learning. 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. The three skill-based training modules with a hands-on project include: 1) 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 (Project - Optimizing an ML Pipeline in Azure)., 2) Machine Learning Operations - 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 (Project - Operationalizing Machine Learning), and 3) Capstone Project - 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 web service and test the model endpoint. Prior experience with Python, Machine Learning, and Statistics is recommended.
Sign-up today (teams & execs welcome): https://tinyurl.com/2pe8hrvj
Much career success, Lawrence E. Wilson - Online Learning Central
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