• Understand Data Platform Modernization
• Choose the right tools for Data Migration
• Migrate SQL Workloads to Azure Virtual Machines
• Migrate SQL Workloads to Azure SQL Databases
• Migrate SQL Workloads to Azure SQL Database Managed Instance

Before attending this course, you should have experience of using Python to work with data and some knowledge of machine learning concepts.

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

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

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

Lab : Getting Started with Azure Databricks

Lab : Working with Data in Azure Databricks

Module 2: Training and Evaluating Machine Learning Models

In this module, you will learn how to use Azure Databricks to prepare data for modelling, and 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

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
• Managing Models

Lab : Using MLflow to Track Experiments

Lab : Managing 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

Lessons

• Tracking Experiments with Azure Machine Learning
• Deploying Models

Lab : Deploying Models in Azure Machine Learning

Lab : Running Experiments in Azure Machine Learning