R Programming Tutorial

In this tutorial, you will learn about different factors that are taken into consideration before choosing your Analytics Platform both at the organization and individual level.

In this tutorial, you'll learn the importance of IDEs, how to set-up Atom, and download packages.

This small tutorial is meant to introduce you to the basics of machine learning in R: it will show you how to use R to work with KNN.

Learn how to import CSV, Excel, JSON, SQL databases, XML, and more into R using readr, readxl, haven, data.table, and other popular packages.

A tutorial on loops in R that looks at the constructs available in R for looping. Discover alternatives using R's vectorization feature.

In this tutorial, the reader will learn the Monte Carlo methodology and its applications in data science, like integral approximation, and parameter estimation.

In this tutorial, you'll learn to join multiple datasets in R.

Practice autocorrelation in R by using course material from DataCamp's Introduction to Time Series Analysis course.

Practice basic programming skills in R by using course material from DataCamp's free Model a Quantitative Trading Strategy in R course.

Learn Time Series Analysis with R along with using a package in R for forecasting to fit the real-time series to match the optimal model.

This tutorial takes course material from DataCamp's Machine Learning Toolbox course and allows you to practice confusion matrices in R.

This tutorial takes course material from DataCamp's Introduction to R for Finance course and allows you to practice Data Frames.