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.

This course introduces key concepts to proficiently work with data - data cleaning, preprocessing, manipulation, transformation, and core concepts of data visualization and interpretation. You'll also work through examples with a provided dataset.

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.

As working with huge numeric datasets becomes the norm, using the right tools and libraries to work with the data becomes very important. NumPy allows data analysts and data scientists to work with multi-dimensional data to solve these problems.

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.

Learn how to use subqueries to combine multiple SELECT statements and compose nested queries.

Get started by writing simple queries in Kusto Query Language (KQL) to explore and gain insights from your data. Learn how to use the operators take, project, where, count, sort, and others.