Implementing a Machine Learning Solution with Microsoft Azure Databricks

DP090 - Version:1
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.
Intended audience
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
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  • Module 1: Introduction to Azure Databricks
    • Getting Started with Azure Databricks
    • Working with Data in Azure Databricks
  • Module 2: Training and Evaluating Machine Learning Models
    • Preparing Data for Machine Learning
    • Training a Machine Learning Model
  • Module 3: Managing Experiments and Models
    • Using MLflow to Track Experiments
    • Managing Models
  • Module 4: Integrating Azure Databricks and Azure Machine Learning
    • Tracking Experiments with Azure Machine Learning
    • Deploying Models
  • 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:1613 - 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