skill track

R Programming

Learn how to code like a programmer in this beginner’s track. First, you’ll learn how to work with common data structures in R like vectors, matrices, and data frames before expanding your skills by mastering conditional statements, loops, and vectorized functions. You’ll then discover how to optimize your code using code profiling and benchmarking. Finally, you'll get to grips with the fundamentals of parallel programming, including reproducibility, generating random numbers, and load balancing. By the end of this track, you’ll be ready to tackle more complex tasks including advanced data visualization and machine learning.

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1
R
Introduction to R
Master the basics of data analysis by manipulating common data structures such as vectors, matrices, and data frames.
4 hours
Jonathan Cornelissen Headshot

Jonathan Cornelissen

Co-founder of DataCamp

2
R
Intermediate R
Continue your journey to becoming an R ninja by learning about conditional statements, loops, and vector functions.
6 hours
Filip Schouwenaars Headshot

Filip Schouwenaars

Data Science Instructor at DataCamp

3
R
Writing Efficient R Code
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.
4 hours
Colin Gillespie Headshot

Colin Gillespie

Assoc Prof at Newcastle University, Consultant at Jumping Rivers

4
R
Parallel Programming in R
This course covers in detail the tools available in R for parallel computing.
4 hours
Hana Sevcikova Headshot

Hana Sevcikova

Senior Research Scientist, University of Washington

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