This course explores the key aspects and solutions related to designing a data protection strategy for your organization using Azure services.

A well-designed application health model gives you contextualized observability by using metrics and thresholds, which you consider important for your mission-critical workload.

Learn how to design a model training solution for machine learning projects.

Learn about machine learning operations or MLOps to bring a model from development to production. Identify options for monitoring and retraining when preparing a model for production.

There are many options on Azure to train and consume machine learning models. Which service best fits your scenario can depend on a myriad of factors. Learn how to identify important requirements and when to use which service when you want to use machine learning models.

Learn how to design a model deployment solution and how the requirements of the deployed model can affect the way you train a model.

This course will teach you how to design a data model with Power BI.

Learn how Azure Synapse Analytics enables you to build Data Warehouses using modern architecture patterns.

The monitoring of an identity solution is critical to every environment. This course covers how to monitor AD, Azure AD, and other components used in a hybrid identity solution.

Understanding what insight you have into available cloud services is critical to architecting the right monitoring strategy. This course looks at the key monitoring technologies in Microsoft Azure to gain the maximum insight into your environment.

This module will demonstrate how Viva Glint helps organizations design a people-centric measurement strategy through our validated taxonomy of measures and robust benchmarks.

In this module, you'll learn how to create a data model with Azure data studio. You'll create indexes and tables and use data types to help develop your applications.