Programming with R

Programming with R

Specifically deepen your knowledge and enter a whole new world of functions. In our two-day training advanced R users learn the basics of functional and object oriented programming. Additionally, we introduce the development of R packages.  The training aims at the provision of competences that allow you to efficiently code R projects on your own or as part of a team.

Data Science Venn Diagramm by Drew Conway from http://drewconway.com/the-lab/

Functional programming: Basically R is a functional programming language. This means the function is the central element of software and analyses. In this module we deal intensively with writing and testing functions in R. We provide you with the necessary knowledge and best practices in order to set your automated analyses on a solid basis.

Object-oriented programming: Object-oriented programming has become the industry standard in software development. R offers various systems to meet this standard. After giving an overview of these systems we will deal in particular with so called S3 classes and methods. S3 is not only easy to learn but also the most frequently used system in R. After taking this module you’ll be able to handle new packages more quickly and develop intuitive tools by yourself.

R packages: The sales argument for R is the availability of packages. Even if you don’t plan to publish new tools or methods on CRAN, package development might still be relevant for you. The advantage is obvious: you can simply pass on your functions to your colleagues or customers. The framework of a package ensures that all required dependencies are available. In addition, it facilitates documentation and helps you wrap automated reports and tools in a solid structure. Our data science experts strongly follow the community standards for package development and show you a development strategy to publish your packages at any time.

Knowledge: This module requires good knowledge of the R programming language. This means, apart from the absolute basics in R, you should already have gained quite some experience working independently with R. Experience in writing your own functions is not a prerequisite for this module, however, corresponding prior knowledge (in R or another programming language) might be helpful.

Hard- and software: You will need a Laptop with the current versions of R, RStudio as well as Rtools if you're using Windows. The statistical programming environment R and Rtools can be downloaded from the website of the Comprehensive R Archive Network. The free desktop version of RStudio is available on the website of RStudio.

Steffen Wagner

Steffen is co-founder of INWT. He specializes in predictive analytics, online marketing, and customer relationship management. He holds a Ph.D. in physics and gives insights into his data science work as a lecturer in the joint master’s program in statistics offered by a consortium of Berlin universities.

Sebastian Warnholz

Sebastian supports the predictive analytics team and works at the interface between software development and data science. He holds a Ph.D. in statistics and is a consultant and instructor at INWT with many years of teaching and business experience.


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