Data Science Tutorials

Discover the main differences between Python’s pandas and polars libraries for data science

Discover what Git Rebase is and how to use it in your data science workflows.

In this tutorial, you'll learn how to install MySQL, create databases, and create tables, along with much more.

With this beginner tutorial, you'll start to explore PEP-8, Python's style guide, so that you can start formatting your code correctly to maximize its readability!

In this article, we will introduce you to JupyterLab, one of the most popular IDE for data science.

In this tutorial, you'll learn about the use of the apply functions in R, its variants, and a few of its relatives applied to different data structures.

Discover how to create, connect to and manage PostgreSQL databases using Python’s psycopg2 package.

In this tutorial, you’ll learn about multi-indices for pandas DataFrames and how they arise naturally from groupby operations on real-world data sets.

Discover what R functions are, the different type of functions in R, and how to create your own functions in R.

Learn what k-means is and discover why it’s one of the most used clustering algorithms in data science

Learn how to use ChatGPT in a real-life end-to-end data science project. We will use it for project planning, data analysis, data preprocessing, model selection, hyperparameter tuning, developing a web app, and deploying it on the Spaces.

Discover all about logistic regression: how it differs from linear regression, how to fit and evaluate these models it in R with the glm() function and more!