Data Science Tutorials

A step-by-step guide to easily deploying a Facebook Messenger chatbot with Python, using Flask, requests and ngrok.

Explore web scraping in R with rvest with a real-life project: extract, preprocess and analyze Trustpilot reviews with tidyverse and tidyquant, and much more!

Analyze poker hands with Python and easily implement statistical concepts such as combinations, permutations, (in)dependent events and expected value.

Boost your machine learning results and discover ensembles in R with the SuperLearner package: learn about the Random Forest algorithm, bagging, and much more!

Discover active learning, a case of semi-supervised machine learning: from its definition and its benefits, to applications and modern research into it.

Implement a small blockchain in R and learn more about what a blockchain looks like and some of the core concepts behind it!

Learn about Python tuples: what they are, how to create them, when to use them, what operations you perform on them and various functions you should know.

Learn to set up a data science environment on Google Cloud: create an instance on Google Compute Engine, install Anaconda and run Jupyter notebooks!

Dive into the lyrics of Prince's music with R: use text mining and Exploratory Data Analysis (EDA) to shed insight on The Artist's career.

In this tutorial, data science meets Search Engine Marketing: learn to create Google AdWords campaigns by generating keywords and ad templates with Python!

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 tutorial, you’ll see what transfer learning is, what some of its applications are and why it is critical skill as a data scientist.