Course Description

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, as well as integrate Databricks machine learning processes with Azure Machine Learning.

Public Profile

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

Items in this collection

• Introduction to Azure Databricks (7 Units)
• Working with data in Azure Databricks (7 Units)
• Preparing data for machine learning with Azure Databricks (9 Units)
• Training a machine learning model with Azure Databricks (7 Units)
• Using MLflow to track experiments in Azure Databricks (7 Units)
• Managing machine learning models in Azure Databricks (7 Units)
• Track Azure Databricks experiments in Azure Machine Learning (8 Units)
• Deploy Azure Databricks models to Azure Machine Learning (8 Units)

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

• 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 workspace and cluster

• Using Azure Databricks to work with data

Module 2: Training and evaluation of Machine Learning models

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

Lessons

• Preparing data for machine learning

• Training a Machine Learning model

Laboratory: Training a Machine Learning model

Lab: Preparing data for machine learning

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

• Preparing data for modeling

• Train and validate a Machine Learning model

Module 3: Experiment and model management

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

Lessons

• Using MLflow to track experiments

• Model management

Lab: Using MLflow to track experiments

Lab: Model Management

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 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

Previous requirements

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

• Creating Machine Learning Models

Language

• English course
• Labs: English