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Big Data in 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.

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1
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
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
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
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

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