DP-3014 Implementing a Machine Learning solution with Azure Databricks

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Course Overview

Azure Databricks is a fully managed, cloud-based data analytics platform, which empowers developers to accelerate AI and innovation by simplifying the process of building enterprise-grade data applications. Built as a joint effort by Microsoft and the team that started Apache Spark, Azure Databricks provides data science, engineering, and analytical teams with a single platform for big data processing and machine learning. In this course, you’ll learn how to use Azure Databricks to train and deploy machine learning models.

Who Should Attend

This course is designed for aspiring data scientists and AI engineers who need to train and manage machine learning models by using Azure Databricks.

Course Outline

1 - Explore Azure Databricks

  • Get started with Azure Databricks
  • Identify Azure Databricks workloads
  • Understand key concepts
  • Data governance using Unity Catalog and Microsoft Purview
  • Module assessment

2 - Use Apache Spark in Azure Databricks

  • Get to know Spark
  • Create a Spark cluster
  • Use Spark in notebooks
  • Use Spark to work with data files
  • Visualize data
  • Module assessment

3 - Train a machine learning model in Azure Databricks

  • Understand principles of machine learning
  • Machine learning in Azure Databricks
  • Prepare data for machine learning
  • Train a machine learning model
  • Evaluate a machine learning model
  • Module assessment

4 - Use MLflow in Azure Databricks

  • Capabilities of MLflow
  • Run experiments with MLflow
  • Register and serve models with MLflow
  • Module assessment

5 - Tune hyperparameters in Azure Databricks

  • Optimize hyperparameters with Hyperopt
  • Review Hyperopt trials
  • Scale Hyperopt trials
  • Module assessment

6 - Use AutoML in Azure Databricks

  • What is AutoML?
  • Use AutoML in the Azure Databricks user interface
  • Use code to run an AutoML experiment
  • Module assessment

7 - Train deep learning models in Azure Databricks

  • Understand deep learning concepts
  • Train models with PyTorch
  • Distribute PyTorch training with TorchDistributor
  • Module assessment

8 - Manage machine learning in production with Azure Databricks

  • Automate your data transformations
  • Explore model development
  • Explore model deployment strategies
  • Explore model versioning and lifecycle management
  • Module assessment

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Class Dates & Times

Class times are listed Eastern time

This is a 1-day class

Register for Class

Register When Time Where How
Register 09/02/2025 9:00AM - 5:00PM Online VILT
Register 11/26/2025 9:00AM - 5:00PM Online VILT

The classes listed are available to all United Training customers and does not reflect, in any way,
the availability or support of technology within the University of Maine System.