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

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

Azure Databricks is a cloud-scalable platform for data analytics and machine learning. In this one-day course, you will 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.

Course aimed at

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.

Elements of the DP-090 formation

• 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)
• Implementing Azure Databricks models in Azure Machine Learning (8 Units)

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

Module 1: Introduction to Azure Databricks

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

Lessons

• Introduction to Azure Databricks

• I 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:

• Provisioning 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

Laboratory: Preparing 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: Management of experiments and models

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

Lessons

• Using MLflow to track experiments

• Model management

Laboratory: Using MLflow to track experiments

Laboratory: Model Management

After completing this module, you will be able to:

• Use MLflow to track experiments

• Model management

Module 4: Integration of 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: Implementing 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 in Azure Databricks to Azure Machine Learning

Prerequisites

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 on Microsoft Learn:

• Creation of Machine Learning models

Language

• Course: English
• Labs: English