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.

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

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

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

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.

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

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 one of the most efficient ways of storing data - relational databases!

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

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

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

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

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

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

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

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

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

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

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

Learn how to work with dates and times in Python.

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

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

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

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.

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