Designing and Implementing a Data Science Solution

Designing and Implementing a Data Science Solution on Azure (Data Scientist)

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.

Who Should Take This Course?

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

What Are The Prerequisites

Required

• 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.
• AZ-900T01: Microsoft Azure Fundamentals (1 Day)

Course Objectives

• Doing Data Science on Azure
• Doing Data Science with Azure Machine Learning service
• Automate Machine Learning with Azure Machine Learning service
• Manage and Monitor Machine Learning Models with the Azure Machine Learning service

Course Outline

Doing Data Science on Azure

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

Doing Data Science with Azure Machine Learning service

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

Automate Machine Learning with Azure Machine Learning service

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

Manage and Monitor Machine Learning Models with the Azure Machine Learning service

• Manage and Monitor Machine Learning Models