Advanced R programming topics
R is the lingua franca of statistical research and data analysis. But in order to get you up and running with R, and to get over the steep learning curve, you need to know how to use it efficiently.
This course is a hands-on course covering the basic toolkit you need to have in order to use R efficiently for data analysis tasks.
It is an intermediate course aimed at users who have the knowledge from the course 'Essential tools for R' and who want to go further to improve and speed up their data analysis tasks.
The following topics will be covered in detail
- The apply family of functions and basic parallel programming for these, vectorisation, regular expressions, string manipulation functions and commonly used functions from the base package. Useful other packages for data manipulation.
- Making a basic reproducible report using Sweave and knitr including tables, graphs and literate programming
- If you want to build your own R package to distribute your work, you need to understand S3 and S4 methods, you need the basics of how generics work as well as R environments, what are namespaces and how are they useful. This will be covered to help you start up and build an R package.
- Basic tips on how to organise and develop R code and test it.
People who have had their initial use of R and want to go one step further.
This covers people using R for a few months already to several years. And more specifically users who want to extend their data manipulation techniques to speed up their day-to-day data analysis tasks.
Researchers from the university interested in making reproducible research reports or users who want to use R as a report generating tool.
R users interested in getting the fundamentals you need to know before you can create your own R package.
Business users who want to learn how to get the maximum out of R by speeding up their code, learn vectorisation, execute the basics of parallel programming and want to learn how to build methods and code which is reproducible in production environments.
Initial experience in R ranging from a few weeks to several years.
Jan Wijffels is the founder of www.bnosac.be - a consultancy company specialised in statistical analysis and data mining. He holds a Master in Commercial Engineering, a MSc in Statistics and a Master in Artificial Intelligence and has been using R for 8 years, developing and deploying R-based solutions for clients in the private sector. He has developed and co-developed the R packages ETLUtils and ffbase.
A .pdf file with the course material will be made available.
Dates and Venue
18 November 2013, 9 hr – 12 hr and 13 hr – 16 hr
19 November 2013, 9 hr – 12 hr and 13hr - 16 hr
Venue: Dekenstraat 2, 3000 Leuven PC room D1
Staff and students KU Leuven and Association KU Leuven: go to: https://icts.kuleuven.be/cursus/
PhD students, non KU Leuven € 160
Non profit/social sector € 250
Private sector € 600
Please click here for details on registration.