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Course Outline

DP-090T00-AC : Implementing a Machine Learning Solution with Microsoft Azure Databrick

Duration : 1 day      

ABOUT THIS COURSE

INTRODUCTION

Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this one-day course, you'll learn how to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.

 

AUDIENCE PROFILE

This course is designed for data scientists with experience of Pythion who need to learn how to apply their data science and machine learning skills on Azure Databricks

 

SKILLS GAINED

  • Provision an Azure Databricks workspace and cluster
  • Use Azure Databricks to train a machine learning model
  • Use MLflow to track experiments and manage machine learning models
  • Integrate Azure Databricks with Azure Machine Learning

 

PREREQUISITES

Before attending this course, you should have experience of using Python to work with data, and some knowledge of machine learning concepts. Before attending this course, complete the following learning path on Microsoft Learn:1613

  • Create machine learning models

 

COURSE OUTLINE

Module 1: Introduction to Azure Databricks

In this module, you will learn how to provision an Azure Databricks workspace and cluster, and use them to work with data.

Lessons

  • Getting Started with Azure Databricks
  • Working with Data in Azure Databricks

 

Lab : Getting Started with Azure Databricks

Lab : Working with Data in Azure Databricks

 

After completing this module, you will be able to:

  • Provision an Azure Databricks workspace and cluster
  • Use Azure Databricks to work with data

 

Module 2: Training and Evaluating Machine Learning Models

In this module, you will learn how to use Azure Databricks to prepare data for modeling, and train and validate a machine learning model.

Lessons

  • Preparing Data for Machine Learning
  • Training a Machine Learning Model

 

Lab : Training a Machine Learning Model

Lab : Preparing Data for Machine Learning

 

After completing this module, you will be able to use Azure Databricks to:

  • Prepare data for modeling
  • Train and validate a machine learning model

 

Module 3: Managing Experiments and Models

In this module, you will learn how to use MLflow to track experiments running in Azure Databricks, and how to manage machine learning models.

Lessons

  • Using MLflow to Track Experiments
  • Managing Models

 

Lab : Using MLflow to Track Experiments

Lab : Managing Models

 

After completing this module, you will be able to:

  • Use MLflow to track experiments
  • Manage models

 

Module 4: Integrating Azure Databricks and Azure Machine Learning

In this module, you will learn how to integrate Azure Databricks with Azure Machine Learning

Lessons

  • Tracking Experiments with Azure Machine Learning
  • Deploying Models

 

Lab : Deploying Models in Azure Machine Learning

Lab : Running Experiments in Azure Machine Learning

 

After completing this module, you will be able to:

  • Run Azure Machine Learning experiments on Azure Databricks compute

Deploy models trained on Azure Databricks to Azure Machine Learning