Introduction to R for Data Science

R is a popular programming language for data science and statistics. It is used by professionals and data experts to map marketing trends, develop financial and climate models, and much more. R is used in many fields and industries for both small and big data applications. It is open-source and backed by a huge community that creates new tools and packages every day.

 

Course Topics

Module 1: Introduction to Basics

Take your first steps with R. Discover the basic data types in R and assign your first variable.

Module 2: Vectors

Analyze gambling behavior using vectors. Create, name and select elements from vectors.

Module 3: Matrices

Learn how to work with matrices in R. Do basic computations with them and demonstrate your knowledge by analyzing the Star Wars box office figures.

Module 4: Factors

R stores categorical data in factors. Learn how to create, subset and compare categorical data.

Module 5: Lists

Lists allow you to store components of different types. Learn how to work with lists.

Module 6: Data Frames

When working R, you’ll probably deal with Data Frames all the time. Therefore, you need to know how to create one, select the most interesting parts of it, and order them.

Module 7: Basic Graphics

Discover R’s packages to do graphics and create your own data visualizations