Microsoft Azure AI Engineer: Developing ML Pipelines in Microsoft Azure

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Tim Warner

2:30:54

16 View

01 - Course Overview

01 - Course Overview.mp4

01:01

02 - Understanding Machine Learning Workspaces

02 - Overview.mp4

01:26

03 - Preliminary Definitions.mp4

01:54

04 - The Azure Machine Learning Landscape.mp4

04:49

05 - The Azure Machine Learning Workspace.mp4

03:37

06 - How You Interact with the Azure ML Workspace.mp4

01:26

07 - Demo- Touring the Azure Machine Learning Workspace.mp4

04:10

08 - Demo- Touring Azure Machine Learning Studio.mp4

09:28

09 - Summary.mp4

01:12

03 - Understanding Azure ML Pipelines

10 - Overview.mp4

00:47

11 - Preliminary Definitions.mp4

03:22

12 - The Azure Machine Learning Pipeline.mp4

04:42

13 - Publishing an Azure ML Pipeline.mp4

01:08

14 - Planning an Azure ML Pipeline.mp4

01:07

15 - Demo- Build an Azure ML Pipeline.mp4

09:53

16 - Demo- Run and Publish the ML Pipeline.mp4

05:36

17 - Summary.mp4

01:24

04 - Managing Machine Learning Workspaces

18 - Overview.mp4

00:57

19 - Understand the Azure Machine Learning Workspace.mp4

02:16

20 - Create a Workspace.mp4

01:48

21 - Demo- Deploy an Azure ML Workspace.mp4

05:18

22 - Demo- Getting Familiar with the Workspace.mp4

03:22

23 - Demo- Working with Jupyter Notebooks.mp4

03:41

24 - Role-Based Access Control (RBAC) in Azure.mp4

01:47

25 - Demo- Secure Azure ML with RBAC.mp4

02:23

26 - Demo- Create and Test a Custom RBAC Role.mp4

06:11

27 - Summary.mp4

01:45

05 - Implementing AI Pipelines

28 - Overview.mp4

00:47

29 - The Azure ML Pipeline Deployment Process.mp4

02:57

30 - Demo- Set up Our Workspace Environment.mp4

06:22

31 - Demo- Run an Experiment with the Python SDK.mp4

08:26

32 - The Azure Data Science Virtual Machine.mp4

03:20

33 - Demo- Deploy an Azure Data Science VM.mp4

05:45

34 - Summary.mp4

00:53

06 - Managing Experiments

35 - Overview.mp4

01:04

36 - Datastore vs. Dataset.mp4

04:46

37 - Automated Machine Learning.mp4

02:06

38 - Demo- Prepare a Datastore.mp4

03:42

39 - Demo- Prepare a Dataset.mp4

02:25

40 - Demo- Create an Automated ML Experiment.mp4

02:22

41 - Demo- Deploy the Best ML Model.mp4

01:55

42 - Summary.mp4

00:55

07 - Managing Data Flow and Logging

43 - Overview.mp4

00:35

44 - Monitoring the ML Model Training Process.mp4

01:20

45 - Demo- Monitoring Experiments in Azure Machine Learning Studio.mp4

02:09

46 - Demo- Using the Azure ML Pyhon SDK to Monitor Model Training.mp4

03:11

47 - Monitoring the Azure Machine Learning Service.mp4

00:56

48 - Demo- Plotting Azure ML Resource Metrics and Raising Alerts.mp4

04:19

49 - Demo- Querying Azure ML Log Data.mp4

02:37

50 - Summary.mp4

01:32

Description

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.

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Microsoft Azure

Tim Warner

Instructor's Courses

Timothy Warner is a Microsoft Most Valuable Professional (MVP) in Cloud and Datacenter Management who is based in Nashville, TN. His professional specialties include Microsoft Azure, cross-platform PowerShell, and all things Windows Server-related. You can reach Tim via Twitter (@TechTrainerTim), LinkedIn or his blog, AzureDepot.com.

Pluralsight

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Pluralsight, LLC is an American privately held online education company that offers a variety of video training courses for software developers, IT administrators, and creative professionals through its website. Founded in 2004 by Aaron Skonnard, Keith Brown, Fritz Onion, and Bill Williams, the company has its headquarters in Farmington, Utah. As of July 2018, it uses more than 1,400 subject-matter experts as authors, and offers more than 7,000 courses in its catalog. Since first moving its courses online in 2007, the company has expanded, developing a full enterprise platform, and adding skills assessment modules.