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.

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.

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.

Explore the use of generative artificial intelligence (AI) models for natural language processing (NLP) in Azure Machine Learning.

Learn how to automate code checks whenever you update code for machine learning workloads.

Designing reports for enterprise scale requires more than just connecting to data. Understanding semantic models and strategies for scalability and optimization are key to a successful enterprise implementation. This learning path helps you prepare for the Fabric Analytics Engineer Certification.

Learn how to manipulate and visualize categorical data using pandas and seaborn.

Learn the essentials of parsing, manipulating and computing with dates and times in R.

This course will show you how to integrate spatial data into your Python Data Science workflow.

Learn how to use advanced Transact-SQL features to fetch and transform data in your databases.

Learn how to use window functions in Transact-SQL.