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Course
- AI
- Cloud
Microsoft Azure AI Engineer: Developing ML Pipelines in Microsoft Azure
This course is for data pros, developers, and IT pros with different areas of responsibility who need to collaborate effectively on data science projects and iteratively develop repeatable, high-quality machine learning models in Microsoft Azure.
What you'll learn
At the core of being a Microsoft Azure AI engineer rests the need for effective collaboration. In this course, Microsoft Azure AI Engineer: Developing ML Pipelines in Microsoft Azure, you will learn how to develop, deploy, and monitor repeatable, high-quality machine learning models with the Microsoft Azure Machine Learning service. First, you will understand how to create no-code machine learning pipelines using the Azure ML service visual designer. Next, you will explore how to train ML models using Python, Jupyter notebooks, and the Microsoft Azure Machine Learning workspace. Finally, you will discover how to monitor your Azure Machine Learning environments from the perspective of the data scientist and data engineer. When you are finished with this course, you will have a foundational knowledge of the Microsoft Azure Machine Learning service that will help you as you move forward in the Microsoft Azure AI engineer job role.
Table of contents
- Overview | 1m 26s
- Preliminary Definitions | 1m 54s
- The Azure Machine Learning Landscape | 4m 49s
- The Azure Machine Learning Workspace | 3m 37s
- How You Interact with the Azure ML Workspace | 1m 26s
- Demo: Touring the Azure Machine Learning Workspace | 4m 10s
- Demo: Touring Azure Machine Learning Studio | 9m 28s
- Summary | 1m 12s
About the author
Timothy Warner is a Microsoft Most Valuable Professional (MVP) in Cloud and Datacenter Management who is based in Nashville, TN.
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