DP-090T00 - Implementing a Machine Learning Solution with Microsoft Azure Databricks

DP-090T00 - Implementing a Machine Learning Solution with Microsoft Azure Databricks

Course Length: 1 day
Delivery Methods: Available as private class only
Course Overview

Azure Databricks is a cloud-scale platform for data analytics and machine learning. In this 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.

This course is designed for data scientists with experience of Python who need to learn how to apply their data science and machine learning skills on Azure Databricks

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Course Benefits
  • 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 Certified Partner

Webucator is a Microsoft Certified Partner for Learning Solutions (CPLS). This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).

Course Outline
  1. Introduction to Azure Databricks
    In this lesson, you will learn how to provision an Azure Databricks workspace and cluster, and use them to work with data.
    1. Getting Started with Azure Databricks
    2. Working with Data in Azure Databricks
    3. On completing this lesson, you will have learned to:
      • Provision an Azure Databricks workspace and cluster
      • Use Azure Databricks to work with data
  2. Training and Evaluating Machine Learning Models
    In this lesson, you will learn how to use Azure Databricks to prepare data for modeling, and train and validate a machine learning model.
    1. Preparing Data for Machine Learning
    2. Training a Machine Learning Model
    3. On completing this lesson, you will have learned to:
      • Prepare data for modeling
      • Train and validate a machine learning model
  3. Managing Experiments and Models
    In this lesson, you will learn how to use MLflow to track experiments running in Azure Databricks, and how to manage machine learning models.
    1. Using MLflow to Track Experiments
    2. Managing Models
    3. On completing this lesson, you will have learned to:
      • Use MLflow to track experiments
      • Manage models
  4. Integrating Azure Databricks and Azure Machine Learning
    In this lesson, you will learn how to integrate Azure Databricks with Azure Machine Learning
    1. Tracking Experiments with Azure Machine Learning
    2. Deploying Models
    3. On completing this lesson, you will have learned to:
      • Run Azure Machine Learning experiments on Azure Databricks compute
      • Deploy models trained on Azure Databricks to Azure Machine Learning

Course Labs

  1. Getting Started with Azure Databricks
  2. Working with Data in Azure Databricks
  3. Training a Machine Learning Model
  4. Preparing Data for Machine Learning
  5. Using MLflow to Track Experiments
  6. Managing Models
  7. Deploying Models in Azure Machine Learning
  8. Running Experiments in Azure Machine Learning
Class Materials

Each student will receive a comprehensive set of materials, including course notes and all the class examples.

Class Prerequisites

Experience in the following is required for this Azure class:

  • Experience using Python to work with data and some knowledge of machine learning concepts.
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  • Private Class for your Team
  • Online or On-location
  • Customizable
  • Expert Instructors
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