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Scalable Data Processing in R

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Certification

Scalable Data Processing in R

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

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Description

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Features

This course includes

Duration

4 hours
Video Content
4 hours
Level
Intermediate
Instruction Type
Self Paced
Delivery Method
Online
Available on
Mobile, Desktop, Laptop
Accessibility
Limited Access
Language
English
Subtitles
English

Skills

Real-time Data ProcessingData ManagementData AnalysisData Manipulation Language

Learning Goals

You’ll learn tools for processing, exploring, and analyzing data directly from disk
You’ll also implement the split-apply-combine approach and learn how to write scalable code using the bigmemory and iotools packages
In this course, you'll make use of the Federal Housing Finance Agency's data

Course Content

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Prerequisites/Requirements

Writing Efficient R Code

Instructors

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Michael Kane

Assistant Professor at Yale University

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Simon Urbanek

Member of the R-Core; Lead Inventive Scientist at AT&T Labs Research

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Course Overview

Case Studies, Hands-On Training, Instructor-Moderated Discussions

Post course interactions

Virtual labs

Case-Based Learning

CapStone project

International faculty

Reviews

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Course Cover

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