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.

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.

After completing this course, you will be able to:

• 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

Module 1: Introduction to Azure Data bricks in this module, you will learn how to provision an Azure Databricks workspace and cluster and use them to work with data. Lesson

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

Lab: Getting Started with Azure Data bricks Lab: Working with Data in Azure Data bricks 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. Lesson

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

Lab: Preparing Data for Machine Learning Lab: Training a Machine Learning Model 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. Lesson

• 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 Lesson

• Tracking Experiments with Azure Machine Learning
• Deploying Models

Lab: Running Experiments in Azure Machine Learning Lab: Deploying Models 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