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Microsoft

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

  • Duration: 1 days
  • Job Role: Data Scientist

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

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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.

Prerequisites

  • 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.

Course outline

Module 1: Introduction to Azure Databricks
Module Overview

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 Sessions

Getting Started with Azure Databricks
Working with Data in Azure Databricks

Lab Lessons

Lab lessons not available

After completing this module, students 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
Module Overview

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 Sessions

Training a Machine Learning Model
Preparing Data for Machine Learning

Lab Lessons

Lab lessons not available

After completing this module, students will be able to:

Prepare data for modeling.
Train and validate a machine learning model.

Module 3: Managing Experiments and Models
Module Overview

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 Sessions

Using MLflow to Track Experiments
Managing Models

Lab Lessons

Lab lessons not available

After completing this module, students will be able to:

Use MLflow to track experiments.
Manage models.

Module 4: Integrating Azure Databricks and Azure Machine Learning
Module Overview

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 Sessions

Deploying Models in Azure Machine Learning
Running Experiments in Azure Machine Learning

Lab Lessons

Lab lessons not available

After completing this module, students will be able to:

Run Azure Machine Learning experiments on Azure Databricks compute.
Deploy models trained on Azure Databricks to Azure Machine Learning.

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