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.
Course info
Rating
(15)
Level
Beginner
Updated
Dec 10, 2019
Duration
2h 30m
Table of contents
Course Overview
Understanding Machine Learning Workspaces
Understanding Azure ML Pipelines
Managing Machine Learning Workspaces
Implementing AI Pipelines
Managing Experiments
Managing Data Flow and Logging
Description
Course info
Rating
(15)
Level
Beginner
Updated
Dec 10, 2019
Duration
2h 30m
Description

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.

About the author
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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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hi everyone, my name is Tim Warner. Welcome to my course, Microsoft Azure AI Engineer: Developing ML Pipelines in Microsoft Azure. I'm a Pluralsight staff author, Microsoft MVP, and Microsoft Azure Solutions Architect This beginner‑level course is for data scientists, developers, and IT professionals who need to be able to collaborate effectively on data science projects, as well as to iteratively develop, deploy, and monitor repeatable, high‑quality machine learning models in Microsoft Azure. By the end of the course, you'll understand how to use Azure Machine Learning tools to perform automated, as well as manual machine learning experiments. You'll also learn how to enforce least privilege security and monitor consumption and performance. I hope you'll join me on this journey to master the Azure Machine Learning service in our Microsoft Azure AI Engineer: Developing ML Pipelines in Microsoft Azure course, at Pluralsight.