Catalog > All Topics

Designing and Implementing a Data Science Solution on Azure (DP-100)

Microsoft
3 Days
Download Course Outline
$1,964.00
Request a Quote
Credit not applicable
Share
Schedule
Export to CSV
  • No schedule events found for this course.
      • PC
        Private Class
        Privately train a group of your employees at your facility, virtually, or any of our locations.
    Request
  • LCLive Classroom
    Live Classroom
    Learn and interact with your instructor and peers in-person in our classrooms.
  • VCVirtual Classroom
    Virtual Classroom
    Attend any of our instructor-led classes virtually regardless of your physical location.
  • PCPrivate Class
    Private Class
    Privately train a group of your employees at your facility, virtually, or any of our locations.
  • GTRGuaranteed to Run
    Guaranteed to Run
    GTR classes are guaranteed to run as promised and delivered.
Course Summary
Show All

Description

Gain the necessary knowledge about how to use Azure services to develop, train, and deploy, machine learning solutions. The course starts with an overview of Azure services that support data science. From there, it focuses on using Azure's premier data science service, Azure Machine Learning service, to automate the data science pipeline. This course is focused on Azure and does not teach the student how to do data science. It is assumed students already know that.

Objectives

This role is responsible for solving the business problem that initiated the project. While the Data Engineer will prepare the data to be used for the models, the Data Scientist determines what data is needed for model training, creates model features from the data, determines what machine learning model to use, trains and evaluates the model, and often has involvement in model deployment. Often the data scientist needs to evaluate multiple models to determine which performs the best.

Prerequisites

Before attending this course, students must have:

  • Azure Fundamentals
  • Understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one.
  • How to program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib, and seaborn.

Who Should Attend

This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models.

Outline

1 - DOING DATA SCIENCE ON AZURE

  • Introduce the Data Science Process
  • Overview of Azure Data Science Options
  • Introduce Azure Notebooks

2 - DOING DATA SCIENCE WITH AZURE MACHINE LEARNING SERVICE

  • Introduce Azure Machine Learning (AML) service
  • Register and deploy ML models with AML service

3 - AUTOMATE MACHINE LEARNING WITH AZURE MACHINE LEARNING SERVICE

  • Automate Machine Learning Model Selection
  • Automate Hyperparameter Tuning with HyperDrive

4 - MANAGE AND MONITOR MACHINE LEARNING MODELS WITH THE AZURE MACHINE LEARNING SERVICE

  • Manage and Monitor Machine Learning Models