DP-100 Part 1 - Preparation

By Brian Roehm

Prepare for designing and implementing a data science solution on the Azure (DP-100) certification exam with machine learning experiments.

8 hours
  • 42 Lessons
  • 4 Hands-On Labs

About the course

In this course, we focus on the preparation needed to begin Azure Machine Learning experiments. This course is part one of a three-part series in preparation for the DP-100 exam.

We will examine:

  • An Introduction to Azure Machine Learning
  • Create an Azure Machine Learning Workspace
  • Manage Experiment Compute Contexts
  • Design the Data Preparation Flow
  • Manage Data Objects in an Azure Machine Learning Workspace
  • Chapter 1 6 Lessons Introduction 14:27

    An Important Note About A Cloud Guru and Linux Academy Courses

    1:19

    Course Introduction

    2:50

    About the Training Architect

    1:05

    Using the DP-100 Essentials Guide

    1:26

    About the Exam

    4:30

    A Note on Data Science and Mathematics

    3:17
  • Chapter 2 8 Lessons An Introduction to Azure Machine Learning 44:39

    An Overview of the Data Science Lifecycle

    8:51

    Quantify the Business Problem

    5:35

    The Basics of Azure Machine Learning

    4:20

    An Introduction to Azure Machine Learning Development Environments

    6:54

    Azure Notebook

    7:52

    Jupyter Notebooks

    5:28

    Zeppelin Notebooks

    2:20

    Exam Essentials and References - AML Introduction

    3:19
  • Chapter 3 8 Lessons Create an Azure Machine Learning Workspace 46:16

    An Introduction to the Azure Machine Learning Workspace

    5:08

    Accompanying Resources with Azure Machine Learning Workspaces

    7:46

    Access Control (IAM)

    6:30

    Create an Azure Machine Learning Workspace

    2:54

    Configure Workspace Settings

    9:30

    Manage a Workspace by Using Azure Machine Learning Studio

    11:09

    Exam Essentials and References - AML Workspace Creation

    3:19

    Create an Azure Machine Learning Workspace

    0:00 Hands-On Lab
  • Chapter 4 5 Lessons Manage Experiment Compute Contexts 19:55

    An Overview of Experiments in Azure Machine Learning

    5:38

    Create a Compute Instance

    3:33

    Create Compute Targets for Experiments and Training

    8:41

    Exam Essentials and References - AML Compute

    2:03

    Create an Experiment in Azure Machine Learning

    0:00 Hands-On Lab
  • Chapter 5 6 Lessons Design the Data Preparation Flow 35:24

    Azure Data Factory

    6:00

    Spark

    9:00

    Azure Machine Learning Versus HDInsight with Spark Cluster

    4:45

    Azure Databricks

    8:26

    Docker

    7:13

    Storing Container Data in Azure Blob Storage

    0:00 Hands-On Lab
  • Chapter 6 7 Lessons Manage Data Objects in an Azure Machine Learning Workspace 50:22

    Pipelines in Azure Machine Learning

    14:50

    Datasets and Dataset Management

    7:34

    Register and Maintain Data Stores

    6:30

    Create and Manage Datasets

    8:39

    A Word on Data Drift

    7:20

    Exam Essentials and References - AML Data Management

    5:29

    Create An Azure Machine Learning Pipeline

    0:00 Hands-On Lab
  • Chapter 7 2 Lessons Course Conclusion 6:50

    Review and Final Notes

    3:48

    What's Next

    3:02

What you will need

  • AZ-900

What are Hands-on Labs

What's the difference between theoretical knowledge and real skills? Practical real-world experience. That's where Hands-on Labs come in! Hands-on Labs are guided, interactive experiences that help you learn and practice real-world scenarios in real cloud environments. Hands-on Labs are seamlessly integrated in courses, so you can learn by doing.

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