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

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.

• 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)
• Tracking Azure Databricks Experiments in Azure Machine Learning (8 Units)
• Deploying Azure Databricks Models to Azure Machine Learning (8 Units)

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

• Working 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:

• Provisioning an Azure Databricks workspace and cluster

• Using 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 how to 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:

• Preparing 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

• Model Management

Lab: Using MLflow to Track Experiments

Lab: Model Management

After completing this module, you will be able to:

• Using MLflow to track experiments

• Model Management

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

• Implement models

Lab: Deploying 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

• Deploying models trained in Azure Databricks to Azure Machine Learning

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

• Creating Machine Learning Models

• Course: English
• Labs: English