What you’ll learn
After completing this course, students 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
Microsoft Azure at DDLS
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Who is the course for?
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.
We can also deliver and customise this training course for larger groups – saving your organisation time, money and resources. For more information, please contact us on 1800 853 276.
Module 1: Introduction to Azure DatabricksIn this module, you will learn how to provision an Azure Databricks workspace and cluster, and use them to work with data.
Lab : Getting Started with Azure DatabricksLab : Working with Data in Azure Databricks
Module 2: Training and Evaluating Machine Learning ModelsIn this module, you will learn how to use Azure Databricks to prepare data for modeling, and train and validate a machine learning model.
Lab : Training a Machine Learning ModelLab : Preparing Data for Machine Learning
Module 3: Managing Experiments and ModelsIn this module, you will learn how to use MLflow to track experiments running in Azure Databricks, and how to manage machine learning models.
Lab : Using MLflow to Track ExperimentsLab : Managing Models
Module 4: Integrating Azure Databricks and Azure Machine LearningIn this module, you will learn how to integrate Azure Databricks with Azure Machine Learning
Lab : Deploying Models in Azure Machine LearningLab : Running Experiments in Azure Machine Learning
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:
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