Learn how to develop client and server-side programming solutions on Azure Cosmos DB.

Do you want to create your own codeunit and learn how to access the functions within that codeunit? If so, this module is the ideal place to start.

Learn how to work with compute targets and environments in the Azure Machine Learning workspace.

Learn how to work with compute targets in Azure Machine Learning. Compute targets allow you to run your machine learning workloads. Explore how and when you can use a compute instance or compute cluster.

Learn how to work with data in Azure Machine Learning. Whether you want to access data in notebooks or scripts, you can read data directly, through datastores, or data assets.

Relational data warehouses are at the heart of many business intelligence and enterprise analytics solutions. You can use Azure Synapse Analytics to implement highly scalable data warehouses in the cloud.

Tables in a Microsoft Fabric lakehouse are based on the Delta Lake storage format commonly used in Apache Spark. By using the enhanced capabilities of delta tables, you can create advanced analytics solutions.

Customer Insights - Data ingests data from all of your different data sources and unifies them into a single customer profile. In this module, learn about working with Customer Insights - Data.

Learn about entitlements and permission sets and how to extend them in Dynamics 365 Business Central.

Learn how to use environments in Azure Machine Learning to run scripts on any compute target.

Learn how to train, test, and deploy a machine learning model by using environments as part of your machine learning operations (MLOps) strategy.

Do you want to develop extensions for Dynamics 365 Business Central? If you do, this learning path will help you do it by following a set of standards that are used by many developers just like you. We'll discuss different tables you'll encounter, documents, master data and more.