Big Data in R

Track Description

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.

Prerequisites

There are no prerequisites for this track

Course
1
Writing Efficient R Code
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Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.
Course
2
Visualizing Big Data with Trelliscope in R
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Learn how to visualize big data in R using ggplot2 and trelliscopejs.
Learn how to visualize big data in R using ggplot2 and trelliscopejs.
Course
3
Scalable Data Processing in R
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Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.
Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.
Course
4
Introduction to Spark with sparklyr in R
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Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.
Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

Big Data in R

4 Courses

Track
Complete

Earn Statement of Accomplishment

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Frequently asked questions

Is this Track suitable for beginners?

Yes! This Track is suitable for anyone looking to take their Big Data journey to the next level, regardless of their level of experience.

What is the programming language of this Track?

This Track is programmed in R.

Which jobs will benefit from this Track?

This Track will be beneficial to a range of jobs, such as software engineering, data manipulation and administration, data science, web development, and analytics.

How will this Track prepare me for my career?

This Track prepares students to set themselves apart from other candidates by emphasizing on-the-job skills that will prove vital in their job search and in their careers.

How long does it take to complete this Track?

It usually takes 16 hours to complete this track.

What's the difference between a skills track and a career track?

A skills track is designed to teach users specific knowledge and skills, using a combination of theory and practice, while a career track takes a more holistic approach, teaching users the skills to pursue an entire career in the field.

What courses are included in this track?

This track includes the following courses: Scalable Data Processing in R, Writing Efficient R Code, Introduction to Spark with sparklyr in R, Visualizing Big Data with Trelliscope in R.

Big Data in R

Track Description

Big Data in R

Prerequisites

Writing Efficient R Code

Visualizing Big Data with Trelliscope in R

Scalable Data Processing in R

Introduction to Spark with sparklyr in R

Earn Statement of Accomplishment