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Overview

About On-Demand Learning

TechSherpas 365’s On-Demand courses provide you with access to Microsoft official courseware materials and hands-on labs, empowering you to learn at your own pace. On-Demand allows you to design your training around your schedule, budget, and individual learning needs.

On-Demand Learning is a perfect solution for students who are unable to attend traditional instructor-led training due to schedule constraints. You receive the same materials and labs as an instructor-led course, with the added convenience of flexible scheduling and a lower price tag.

This On-Demand Course Includes:

  • Microsoft Official Courseware License with Lifetime Access (and automatic version updates)
  • Access to Hands-on Labs for 180 days
  • Access to 3 hours of Instructor Time (upon request):
    • One-on-one live instructor time geared towards your specific needs
    • Scheduled in 1-hour increments

About This Course

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

Job role: Data Scientist

Features: none

Skills gained

  • 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

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

This course will teach the basics of Microsoft’s dialect of the standard SQL language: Transact-SQL. Topics include both querying and modifying data in relational databases that are hosted in Microsoft SQL Server-based database systems, including: Microsoft SQL Server, Azure SQL Database and, Azure Synapse Analytics.

Audience Profile

This course can be valuable for anyone who needs to write basic SQL or Transact-SQL queries. This includes anyone working with data as a data analyst, a data engineer, a data scientist, a database administrator or a database developer. It can also be useful for others peripherally involved with data, or wanting to learn more about working with data such as solution architects, students and technology managers.

Job role: Database Administrator

Features: none

Skills gained

  • Use SQL Server query tools
  • Write SELECT statements to retrieve columns from one or more tables
  • Sort and filter selected data
  • Use built-in functions to returned data values
  • Create groups of data and aggregate the results
  • Modify data with Transact-SQL using INSERT, UPDATE, DELETE and MERGE

 

Description

Module 1: Introduction to Azure Databricks

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 : Getting Started with Azure Databricks

Lab : Working with Data in Azure Databricks

After completing this module, you 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

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 : Training a Machine Learning Model

Lab : Preparing Data for Machine Learning

After completing this module, you will be able to use Azure Databricks to:

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

Module 3: Managing Experiments and Models

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 : Using MLflow to Track Experiments

Lab : Managing Models

After completing this module, you will be able to:

  • Use MLflow to track experiments
  • Manage models

Module 4: Integrating Azure Databricks and Azure Machine Learning

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 : Deploying Models in Azure Machine Learning

Lab : Running Experiments in Azure Machine Learning

After completing this module, you will be able to:

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