Overview
Practical Data Management with R for Social Scientists
Next course runs from 9 October - 5 November 2017
Overview
Practical Data Management with R for Social Scientists
Next course runs from 9 October - 5 November 2017
Course description
Data management - the art and science of collecting, cleaning, and manipulating data - is one of the most essential research skills for social scientists.
This course will seek to demystify these 'dark arts', and provide you with the foundation to tackle a wide range of practical data management tasks using the R programming language.
By the end of this course, you will possess the programming skills and experience to manage data in a wide variety of formats, in a reproducible manner, at scale.
Learning outcomes
This course will provide you with the foundation to tackle a wide range of practical data management tasks using the R programming language. It will teach you:
- 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
Any questions? - Contact us
For a bulk order of 5 or more learners on any of our courses, you can claim 50% discount. Contact us for more information.
Practical Data Management with R for Social Scientists
Course Instructors
Course Instructors
Course Instructor
How it works
How it works
How It Works
This course is broken up into four units, starting with basic R programming and working up through more advanced data management, web scraping, and finally big data/HPC techniques and issues. Each unit is broken up into a number of discrete topics, with video lectures and supporting materials associated with each topic. At the end of each unit, participants will be given a homework assignment that synthesizes what they have learned in that unit.
Each unit should take about a week, with the earlier units requiring a bit more time. Each topic builds on the previous topics, so it is designed to be completed in order, unless you have previous experience with a topic. In the lectures, Matt provides as much context and explanation for each new concept as possible. If you put in the work, and try out the code yourself, you should have a strong foundation to start working on serious data management tasks in R by the end of the course.
Syllabus
Syllabus
Syllabus
Unit One
Programming and Data Structures in R
As well as introducing you to the course, this unit will teach you:
- How to install R and RStudio
- Basic R programming skills, such as how to write commands in an R script
- How to understand the core data structures you need to manage a huge variety of data
- Data I/O and packages so you can extend the functionality of R
- Looping and conditional statements so you can automate wildly complex tasks
- Functions so you don’t have to write the same code over and over again for similar tasks
Unit Two
Data Management in R
This unit will teach you how to:
- Manage multiple datasets by example
- Convert long and wide format data
- Deal with poorly formated data and/or missing data
- Automate tasks using functions
- Work with and manipulate text data
Unit Three
Automated Data Collection
This unit will give you:
- An overview of web/text scraping and the related legal considerations
- A basic web scraping example so you can learn how to treat a webpage as a messy text document
- An understanding of scraping Twitter
Performance and Scalability
This unit will focus on:
- Giving you an overview of big data and high-performance computing (HPC)
- Teaching you about performant programming
- Wrapping up with a range of next steps and ways to extend your skills
Unit Four
Enroll Now
Enroll Now
Enroll Now
Next course starts 9 October 2017.
Book your place today!