DP-100 Part 1 – Preparation
Azure Training Architect I in Content
In this video, we discuss this course and Microsoft's DP-100 certification exam.
About the Training Architect
Meet your instructor! In this video, I'll introduce myself and provide a little background on my experience.
Using the DP-100 Essentials Guide
In this video, we introduce the DP-100 Essentials Guide, how to navigate it, and how to leverage it to help with exam preparation.
About the Exam
Gain practical tips on what to expect on exam day, details about the exam itself, and how to prepare for the exam both today and on exam day.
A Note on Data Science and Mathematics
This course is designed to help pass the DP-100 exam. In this video, we cover other critical skills for being an outstanding data scientist.
An Introduction to Azure Machine Learning
An Overview of the Data Science Lifecycle
This lesson is a high-level overview of the Data Science Lifecycle. The goal of this video is to introduce you to the concepts of the entire process so that as we get into the details of the components in later videos, you will understand where we are in the Lifecycle process.
Quantify the Business Problem
This video is a deeper look at the first stage and defines the business problem. We will examine the questions that need to be asked and look at how to create SMART objectives.
The Basics of Azure Machine Learning
In this video, we will walk through the larger Azure Machine Learning DevOps Pipeline to provide an understanding of where Azure Machine Learning sits in a typical DevOps pipeline.
An Introduction to Azure Machine Learning Development Environments
This video is our first live look at the Azure Machine Learning Studio. In addition, we will review key terminology that will be used throughout the course.
In this video, we will discuss the differences between Azure Notebooks and notebooks in the Azure Machine Learning service. We will also take a look at the live Azure Machine Learning environment and discuss how to create and navigate from within a notebook.
In this video, I will discuss Jupyter notebooks through the Jupyter.org interface. We will briefly discuss the installation process and then compare and contrast notebooks through Azure Machine Learning Studio, Azure Notebooks, and Jupyter.org.Links from the video:
This video provides a brief introduction to Zeppelin Notebooks and a discussion on Zeppelin versus Jupyter.
Exam Essentials and References - AML Introduction
In this video, we will review key concepts from the section and additional resources to help you prepare for the DP-100.
Create an Azure Machine Learning Workspace
An Introduction to the Azure Machine Learning Workspace
In this video, we introduce the concept of a workspace, discuss the differences between Enterprise and Basic editions, and show how to create a workspace in the Azure Portal.
Accompanying Resources with Azure Machine Learning Workspaces
When you create an Azure Machine Learning workspace, several other resources get created. In this video, we review what those services are and how to access them within the Azure Portal.
Access Control (IAM)
In this video, we build a foundation for Role-Based Access Control (RBAC) and use it to understand Identity Access Management (IAM) in Azure Machine Learning. Along the way, we interact with the Portal to assign a role.
Create an Azure Machine Learning Workspace
In this video, we provide some links to pricing to estimate any potential Machine Learning costs. We also provide a quick walkthrough of workspace creation to demonstrate the process from start to finish.
Configure Workspace Settings
To continue our discussion on Azure Machine Learning workspaces, we will be examining Configuration Settings and focusing on events and reporting. This includes a live look at the Portal and how to access various settings for Machine Learning workspaces.
Manage a Workspace by Using Azure Machine Learning Studio
In this video, we introduce the Azure Machine Learning Studio and Designer. The goal is to provide familiarity with Studio. Each of the topics discussed will be the subject of a much deeper dive and hands-on labs as we move through the DP-100 courses.
Exam Essentials and References - AML Workspace Creation
In this video, we review key concepts from the section and provide a list of links for additional resources.
Manage Experiment Compute Contexts
An Overview of Experiments in Azure Machine Learning
In this video, we introduce the concepts of experiments, provide some basic terminology, and show you what an experiment looks like in the Azure Portal.
Create a Compute Instance
This is a quick dive into how to start up a compute instance in the Azure Portal, review pricing, and pause or restart instances.
Create Compute Targets for Experiments and Training
Continuing our discussion on compute, we review compute targets, training clusters, and do a demonstration on attaching a databricks workspace as an attached compute.
Exam Essentials and References - AML Compute
This provides a review of key concepts from the section and a list of exam reference links to review Microsoft documentation.
Design the Data Preparation Flow
Azure Data Factory
Azure Data Factory is an orchestration service that can have impacts on Azure Machine Learning. In this video, we review core concepts of the service to provide a basic background of it for the DP-100.
Apache Spark is the underlying technology of many Azure services. In this video, we take a look at Apache Spark, how it operates, and what's necessary to know to provide a better understanding of data engineering and how it interacts with data science.
Azure Machine Learning Versus HDInsight with Spark Cluster
In this lesson, we review Azure Machine Learning and contrast it to HDInsight with Spark Cluster. This will help provide a better understanding of the key focus areas for Azure Machine Learning on the DP-100.
In this lesson, we take a high-level look at databricks, how it functions in a typical cloud project, and how it interacts with Azure Machine Learning. While it's not likely to be directly on the DP-100, this lesson will provide needed background for any questions mentioning this service.
In this video, we provide an introduction to Docker and containers. We discuss the overall process, key terminology, and how Docker connects with Azure Machine Learning.
Manage Data Objects in an Azure Machine Learning Workspace
Pipelines in Azure Machine Learning
In this video, we discuss Azure Machine Learning pipelines and get a live look in the Azure Portal as to how they function.
Datasets and Dataset Management
In this video, we introduce the concepts of datasets, datastores, data drift, and dataset management. We look at terminology, how the concepts work together, and how we monitor data drift using dataset management.
Register and Maintain Data Stores
In this video, we walk through how to create a new datastore in the Azure Portal. We also provide a walkthrough of Azure SDK code.
Create and Manage Datasets
In this video, we create a dataset in the Azure Portal and take a quick look at the syntax for creating datasets using the Azure Machine Learning SDK.
A Word on Data Drift
In this video, we explore the concept of data drift. Along the way, we will define what data drift is, what causes it, and identify some ways to manage it.
Exam Essentials and References - AML Data Management
In this section review, we identify key concepts necessary for the DP-100.
Review and Final Notes
In this video, I present a quick walkthrough of high-level concepts you need to know and provide some suggestions on preparing for the DP-100 content in this first module.
In this final video we will take a look at next steps in preparing for the DP-100 exam.
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