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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.

Audience profile

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

Job role: Data Scientist

Accessing your courseware and registering attendance with Microsoft

To access your Official Curriculum (MOC) course materials you will need a Microsoft.com/Learn account. In Learn you will also be able to register your completion of the event and receive your achievement badge. You will be issued with a unique code during your event.

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

Create machine learning models

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 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

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.

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:

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.

Lessons

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

Lessons

Tracking Experiments with Azure Machine Learning
Deploying Models

Lab : Deploying 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 on Azure Databricks to Azure Machine Learning

Upcoming Trainings

Join our public courses in our Singapore facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

Classroom / Virtual Classroom

05 July 2024