DP-090: Implementing a Machine Learning Solution with Microsoft Azure Databricks

Course description

Azure Databricks is a cloud-scalable 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, as well as how to integrate Databricks machine learning processes with Azure Machine Learning.

Audience Profile

This course is designed for data scientists with a Python background who need to learn how to apply their data science and machine learning skills to Azure Databricks.
 

Items in this collection

• Introduction to Azure Databricks (7 Units)
• Work with data in Azure Databricks (7 Units)
• Prepare data for machine learning with Azure Databricks (9 Units)
• Training a machine learning model with Azure Databricks (7 Units)
• Using MLflow to track experiments on Azure Databricks (7 Units)
• Managing machine learning models in Azure Databricks (7 Units)
• Tracking of Azure Databricks experiments in Azure Machine Learning (8 Units)
• Implementation of Azure Databricks models in Azure Machine Learning (8 Units)

course outline

Module 1: Introduction to Azure Databricks

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

lessons

• Introduction to Azure Databricks

• Work with data in Azure Databricks

Lab : Introduction to Azure Databricks

Lab : Working with data in Azure Databricks

After completing this module, you will be able to:

• Provision an Azure Databricks cluster and workspace

• Using Azure Databricks to work with data

Module 2: Training and evaluating Machine Learning models

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

lessons

• Preparing the data for machine learning

• Training a Machine Learning model

Lab : Training a Machine Learning Model

Lab : Preparing the data for machine learning

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

• Data preparation for modeling

• Train and validate a machine learning model

Module 3: Managing Experiments and Models

In this module, you'll learn how to use MLflow to track experiments running on Azure Databricks and how to manage Machine Learning models.

lessons

• Using MLflow to track experiments

• Model Management

Lab : Using MLflow to track experiments

Lab : Managing Models

After completing this module, you will be able to:

• Use MLflow to track experiments

• Model Management

Module 4: Azure Databricks and Azure Machine Learning integration

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

lessons

• Track experiments with Azure Machine Learning

• Deploy models

Lab : Deploy models to 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 to Azure Machine Learning models trained on Azure Databricks

Previous requirements

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

• Building Machine Learning models

Language

• English course
• Labs: English