Intensive Training – Implementing a Machine Learning Solution with MS Azure Databricks («DP090»)

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 modeling, and train and validate a machine learning model.
Lessons

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

Lab : Preparing Data for Machine Learning
Lab : Training 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
• 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 : Running Experiments in Azure Machine Learning
Lab : Deploying Models in 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

• Experience using Python to work with data, and some knowledge of machine learning concepts.
• Complete the following learning path on Microsoft Learn: Create machine learning models