- Learn about the data science process and the role of the data scientist.
- Understand how Azure services can support and augment the data science process.
- Learn to use Azure Machine Learning service to automate the data science process end to end.
- Learn about the machine learning pipeline and how the Azure Machine Learning service's AutoML and HyperDrive can automate some of the laborious parts of it.
- Learn how to automatically manage and monitor machine learning models in the Azure Machine Learning service.
In this Designing and Implementing a Data Science Solution on Azure training class, students will 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 assumes students already know data science fundamentals.
This course is aimed at data scientists and those with significant responsibilities in training and deploying machine learning models.
Webucator is a Microsoft Certified Partner for Learning Solutions (CPLS). This class uses official Microsoft courseware and will be delivered by a Microsoft Certified Trainer (MCT).
- 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
Each student will receive a comprehensive set of materials, including course notes and all the class examples.
Experience in the following is required for this Azure class:
- Azure Fundamentals.
- Understanding of data science including how to prepare data, train models, and evaluate competing models to select the best one.
- Ability program in the Python programming language and use the Python libraries: pandas, scikit-learn, matplotlib, and seaborn.