Learn the basics of Python 3.12, one of the most powerful, versatile, and in-demand programming languages today.

Get started with Python for Data Science in this beginner-friendly skill path.

Learn how to code and clean and manipulate data for analysis and visualization with the R programming language.

In this SQL course, you'll learn how to manage large datasets and analyze real data using the standard data management language.

Level up your data storytelling skills by learning how to create dashboards and visualizations in Tableau.

This course introduces important resources for data science, including visualization libraries, deep learning frameworks, and cloud-based environments. It also explores BigML and Google Colab—powerful resources for building and sharing analytics.

Power BI reports often depend on local data sources. This course will teach you use on-premises data gateways to connect the two.

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

This course will teach you about the different types of Data Normalization techniques you can use when preparing your Deep Learning datasets in Machine Learning.

Get started with Large Language Model (LLM) foundations and tokenization. Learn how tokenization is a critical step in NLP and machine learning, and explore techniques for breaking down text data into meaningful components for model training.

Data warehouse in Microsoft Fabric is a comprehensive platform for data and analytics, featuring advanced query processing and full transactional T-SQL capabilities for easy data management and analysis.

In this course, you will learn how to use Data Manager to extract, transform and load data into Qlik Sense for analysis. By the end of the course, you will be able to execute self-service analytics without being dependent on a BI or IT developer.