Data, AI, and Cloud Courses

Learn to clean data as quickly and accurately as possible to help you move from raw data to awesome insights.

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

Data visualization is one of the most desired skills for data analysts. This course allows you to present your findings better using Tableau.

This course dives deeper into the Azures backbone by going into topics like containers, virtual machines and much more.

Learn to write SQL queries to calculate key metrics that businesses use to measure performance.

Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.

Learn Databricks SQL for data engineering, analytics, and real-time data workflows in the lakehouse architecture.

Learn about the power of Databricks Lakehouse and help you scale up your data engineering and machine learning skills.

Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!

Learn to write cleaner, smarter Java code with methods, control flow, and loops.

Discover how to become a data defender and keep data safe and secure with this beginner-friendly interactive course.

In this course you will learn the basics of machine learning for classification.

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

Learn the theory behind responsibly managing your data for any AI project, from start to finish and beyond.

To understand Fabric’s main use cases, you will explore various tools in the seven Fabric experiences.

Discover how to make better business decisions by applying practical data frameworks—no coding required.

Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.

Learn to process, transform, and manipulate images at your will.

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

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

Level up your GitHub skills with our intermediate course on GitHub Projects, Administration, and advanced security features.

What makes LLMs tick? Discover how transformers revolutionized text modeling and kickstarted the generative AI boom.

Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.

Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.

Building on your foundational Power Query in Excel knowledge, this intermediate course takes you to the next level of data transformation mastery

Master text analysis with essential NLP techniques from preprocessing to advanced transformer models.

Build the foundation you need to think statistically and to speak the language of your data.

Learn about string manipulation and become a master at using regular expressions.