Data science courses

Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.

Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

Master the fundamentals of programming in Python. No prior knowledge required!

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.

Get started on the path to exploring and visualizing your own data with the tidyverse, a powerful and popular collection of data science tools within R.

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

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

Learn how to create one of the most efficient ways of storing data - relational databases!

Familiarize yourself with Git for version control. Explore how to track, compare, modify, and revert files, as well as collaborate with colleagues using Git.

Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon!

Dive into the Python ecosystem, discovering modules and packages along with how to write custom functions!

Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.

The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds.

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.

Learn to use SQL Server to perform common data manipulation tasks and master common data manipulation tasks using this database system.

Gain an introduction to Docker and discover its importance in the data professional’s toolkit. Learn about Docker containers, images, and more.

Dive into the exciting world of APIs as we introduce you to the basics of consuming and working with Web APIs using Python.

Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!

Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.

Learn how to work with dates and times in Python.

Learn how to use GitHubs various features, navigate the interface and perform everyday collaborative tasks.

Learn the essentials of VMs, containers, Docker, and Kubernetes. Understand the differences to get started!

Discover the fundamental concepts of object-oriented programming (OOP), building custom classes and objects!

Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.

In this course, you will learn the fundamentals of Kubernetes and deploy and orchestrate containers using Manifests and kubectl instructions.

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

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