Intro


SCROLL DOWN

Intro


Practical Data Management with R for Social Scientists

Practical Data Management with R for Social Scientists
299.00
Start Date:
Buy now

What you'll learn


What you'll learn


What you'll learn on this self-paced online course

Learn how to use R to manage data in a wide variety of formats, in a reproducible manner, at scale.

By the end of this course you will have gained:

  • An understanding of Basic R commands and data structures for manipulating data

  • The ability to read data from multiple formats in and out of R

  • Proficiency using loops, conditional statements, and functions to automate common data management tasks

  • Familiarity with R’s package system for extending its functionality

  • The skills to clean and manage multiple complex datasets

  • The ability to clean and manipulate textual data

  • An understanding of basic web scraping techniques, for both standard web pages and the Twitter API

  • An overview of the techniques and hardware necessary to manage large datasets efficiently

English
15-25 hours to learn
3 months access

Instructor
[[Instructor]]

Price
$[[price]]USD

Enroll a group
Looking to upskill a group of 5 or more learners or get access for your institution? Find out more

Inconvenient Start Date?
Register interest for future dates

Course modules


Course modules


There are five modules in this course

Introduction to R and RStudio

You will learn about: installing R and RStudio, basic R programming skills and five basic data structures.

R Programming Fundamentals

You will learn about: Data I/O and packages, looping and conditional statements, and functions

Data Management in R

You will learn how to: manage multiple datasets by example, work with text data, convert long- and wide-format data and deal with messy data.

Automated Data Collection

You will be given: an overview of web/text scraping and the legal considerations, a basic web scraping example and an understanding of scraping Twitter.

Performance and Scalability

You will be introduced to High Performance Computing and Big Data and learn about performant programming.

Try it out


Try it out


Try it out

 
Icon_55px_21.png
Icon_55px_11.png
Icon_55px_36.png

Testimonials


Testimonials


What our learners say

 
PDM-Testimonials
Ariel Quinio - Ontario Institute for Studies in Education at the University of Toronto

I enrolled in Practical Data Management with R as I continuously seek different ways of looking at and analyzing my research data, and I want to keep abreast of the current trends in data sciences. The instructor did an excellent job. As a teacher Matt Denny was detail-oriented, and employed a variety of teaching modalities including repetition to emphasize important aspects of the lesson, and illustration using examples to apply relevant concepts or procedures to follow. Most of all, I liked the aura of politeness in the way he talked throughout the course while explaining a complex topic. I think he has the qualities of a good teacher as evident during the concluding sections where he was able to inspire, motivate and encourage students to go beyond what this course has to offer.


A Learner on Practical Data Management with R

I wish I had taken this course years ago when I started learning R. I'm much more confident now and I'm not even halfway through the course.

Thank You!

 

Prerequisites


Prerequisites


Prerequisites

Basic computer skills, and some experience working with any sort of statistical analysis software (Excel, SAS, Stata, SPSS) will be helpful.

FAQs


FAQs


Frequently asked questions

How is this course structured?

This course is broken up into five units. Each unit is broken up into a number of discrete topics, with video lectures and supporting materials associated with each topic. Each topic builds on the previous topics, so they are designed to be completed in order, unless you have previous experience with a topic. At the end of each unit, you will be given a homework assignment that synthesizes what you have learned in that unit.

Can I fit the course around my schedule?

We know you’re busy so we don’t set module deadlines. You are free to login and learn whenever suits your schedule. If you are able to commit to a few evenings a week, you will have completed the modules within approximately a month. However, if you have a busy period, you have the flexibility to spread your module completion over a 3 month access period.

How can I get help during the course?

SAGE Campus will help you with any IT or platform issues you might have.

How long will I have access to the course for?

You will have access to the course material for 3 months.

Do learners get a certificate?

All of our courses offer a certificate of completion signed by your instructor. You will be able to download this certificate, from the Learning Platform, when you complete the course.

Can't find what you're looking for? Contact Us

Other Courses


Other Courses


Take a look at our other SAGE Campus courses

Settings


Settings


Featured
Matthew Denny
Matthew Denny

Matt Denny is a PhD Candidate in Political Science and Social Data Analytics, and an NSF Big Data Social Science IGERT Fellow at Penn State University. Matt spends most of his time developing methods for analysing text and network data, which he applies to a wide range of projects related to: U.S. congressional and bureaucratic politics, organizational dynamics, international finance, and more recently, neuroscience. As part of his research, Matt works with a variety of large and complex datasets on a daily basis. Matt has also taught dozens of workshops on data management, high performance computing and “big data” analytics in R. To learn more about Matt Denny, check out his website: www.mjdenny.com

V2 Course Page Tag