Introduction to Python
Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
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 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.
Familiarize yourself with Git for version control. Explore how to track, compare, modify, and revert files, as well as collaborate with colleagues using Git.
Continue to build your modern Data Science skills by learning about iterators and list comprehensions.
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.
Learn to implement distributed data management and machine learning in Spark using the PySpark package.
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.
Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.
Master the fundamentals of programming in Python. No prior knowledge required!
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.
Learn to use best practices to write maintainable, reusable, complex functions with good documentation.
Explore data structures such as linked lists, stacks, queues, hash tables, and graphs; and search and sort algorithms!
Bring your Google Sheets to life by mastering fundamental skills such as formulas, operations, and cell references.
Learn the fundamentals of working with big data with PySpark.
Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.
Learn how to work with dates and times in Python.
Dive into the Python ecosystem, discovering modules and packages along with how to write custom functions!
In this course, you will use T-SQL, the flavor of SQL used in Microsoft's SQL Server for data analysis.
Take your R skills up a notch by learning to write efficient, reusable functions.
Prepare for your next coding interviews in Python.
Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.
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.