Skip to main content
skill track

Big Data with R

R has great ways to handle working with big data including programming in parallel and interfacing with Spark. In this track, you'll learn how to write scalable and efficient R code and ways to visualize it too.

RClock16 hoursLearn4 Courses

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.

Loved by learners at thousands of companies

1
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

2
R
Visualizing Big Data with Trelliscope in R

Learn how to visualize big data in R using ggplot2 and trelliscopejs.

4 hours

Ryan Hafen Headshot

Ryan Hafen

Author of TrelliscopeJS

3
R
Scalable Data Processing in R

Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.

4 hours

Michael Kane Headshot

Michael Kane

Assistant Professor at Yale University

4
R
Introduction to Spark with sparklyr in R

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

4 hours

Richie Cotton Headshot

Richie Cotton

Data Evangelist at DataCamp

Track statement of accomplishment

Instructors

  • Colin Gillespie Headshot
    Colin GillespieAssoc Prof at Newcastle University, Consultant at Jumping RiversSee Profile
  • Ryan Hafen Headshot
    Ryan HafenAuthor of TrelliscopeJSSee Profile
  • Michael Kane Headshot
    Michael KaneAssistant Professor at Yale UniversitySee Profile
  • Simon Urbanek Headshot
    Simon UrbanekMember of the R-Core; Lead Inventive Scientist at AT&T Labs ResearchSee Profile