Data, AI, and Cloud Courses

Build robust, production-grade APIs with FastAPI, mastering HTTP operations, validation, and async execution to create efficient data and ML pipelines.

Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.

Take your R skills up a notch by learning to write efficient, reusable functions.

Learn key object-oriented programming concepts, from basic classes and objects to advanced topics like inheritance and polymorphism.

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

In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.

Learn to create your own Python packages to make your code easier to use and share with others.

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

In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.

Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

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

Master multi-stage builds, Docker networking tools, and Docker Compose for optimal containerized applications!

Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.

Prepare for your next coding interviews in Python.

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

Master SQL Server programming by learning to create, update, and execute functions and stored procedures.

In this course, students will learn to write queries that are both efficient and easy to read and understand.

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

Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.

Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Learn how to pull character strings apart, put them back together and use the stringr package.

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

Learn how to structure your PostgreSQL queries to run in a fraction of the time.

Manage the complexity in your code using object-oriented programming with the S3 and R6 systems.

Build real-world applications with Python—practice using OOP and software engineering principles to write clean and maintainable code.

Master Git’s advanced features to streamline data science and engineering workflows, from complex merging to large-scale project optimization.

Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Use your knowledge of common spreadsheet functions and techniques to explore Python!