DP-100 DESIGNING AND IMPLEMENTING A DATA SCIENCE SOLUTION ON AZURE
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.
Audience
This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models.
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.
Agenda
Module 1: Doing Data Science on Azure
- Overview of Azure Data Science Options
- Introduce Azure Notebooks
Module 2: Doing Data Science with Azure Machine Learning Service
- Introduce Azure Machine Learning (AML) service
- Register and deploy ML models with AML service
Module 3: Automate Machine Learning with Azure Machine Learning Service
- Automate Machine Learning Model Selection
- Automate Hyperparameter Tuning with HyperDrive
Module 4: Manage and Monitor Machine Learning Models with the Azure Machine Learning Service
Manage and Monitor Machine Learning Models
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