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Verena Kunz

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Noemi Hartung
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Advanced R Programming

About
Location:
Online via Zoom
General Topics:
Data Analysis
Course Level:
Advanced
Format:
Workshop
Software used:
R
Duration:
3 days
Language:
English
Fees:
Students: 300 €
Academics: 450 €
Commercial: 900 €
 
Keywords
Additional links
Lecturer(s): Tom Paskhalis

About the lecturer - Tom Paskhalis

Course description

R is the major language for statistical programming and data analysis. In its more than 30 year history it went from an open-source implementation of its commercial predecessor S to being the staple of any data analyst's toolbox. The versatility of R lies in its immense extendibility, something we will discuss in this workshop.
 
This workshop is aimed at participants who already have some experience with R, but would like to further hone their skills in this language. We will cover advanced topics in R programming, such as functional and object-oriented programming, debugging, testing, and parallelization. The workshop's ultimate goal is to provide the participants with a solid foundation of R programming, which will allow them to tackle more complex problems and design efficient work flows for data analysis.


Target group

Participants will find the course useful if:
  • they have been working with R for a while and are looking to take their R skills to the next level to facilitate more complex programming tasks.
  • they wish to write more efficient R code.
  • they want to learn (more) about the power of functional programming.
  • they want to learn more about debugging and testing.
  • they want to write their own R packages.


    • Learning objectives

    By the end of the course participants will:
  • be able to describe core programming concepts, language structures, and design principles.
  • demonstrate deep familiarity with the R programming languages.
  • have the ability to write, execute and debug R scripts.
  • understand the foundations of functional and object-oriented programming in R.
  • be able to design efficient work flows for data analysis.
    •  
    Organisational structure of the course
    This workshop is organized around lectures interspersed with hand-on programming exercises. While lectures are designed to give an overview of the topic, key concepts and their implementations in R, the exercises allow the participants to apply these ideas in practice.


    Prerequisites

    This course covers intermediate and advanced programming in R, and basic familiarity with the key R concepts, such as objects and operators, data types and data manipulation, is assumed.
     
    Participants should therefore have reasonable prior experience with R (e.g. working with R for more than 6 months,
    up to a couple of years) to get the most out of this workshop. Alternatively, extensive knowledge of another statistical software (e.g. Stata/SAS) and some introductory knowledge of R syntax should also work. A short overview of some R fundamentals will be provided at the beginning of the workshop. Some participants with prior experience in statistical analysis/programming who recently took an introductory R workshop (e.g. an “Introduction to R” workshop offered by GESIS) might consider enrolling into this workshop as a follow-up.
     
    Software and hardware requirements
    In this course we will use R (4+) and RStudio integrated develoment environment. Alternatively, you can use Visual Studio Code with R Extension installed.


    Schedule

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