This course is for R users, already applying the tool in real-world applications, who are looking for more efficient and powerful ways to:
- manipulate data and automate their analysis and research
- develop R applications
- improve the performance and scale of their applications
Attendees will be introduced to a range of methods for advanced data processing, speeding up R code, scaling R to hard disk memory, and advanced programming.
This course will cover a range of advanced R topics, including the following.
Advanced data manipulation
- advanced indexing syntax
- string processing with package stringr
- date processing with package lubridate
- SQL in R with sqldf
- data processing and transformation with packages plyr and reshape2.
- efficient data processing and transformation with newly released packages dplyr and tidyr
Speeding up R
- parallelisation with the parallel package
- inline C++ code with the rcpp package
Extending R’s memory: Working with massive objects in secondary memory
- the big family of packages: bigmemory, biganalytics, and others.
Object-oriented programming in R
- R’s S3 and S4 classes
(These may be covered if time permits.)
- using R on a server
- using R in batch mode
- using R on the cloud
- R and Hadoop
Computers running R with practical examples from all core components will be provided to attendees. These may not necessarily be configured for the most advanced topics, which may involve demonstrations only, especially if requiring server or cloud functionality.
This is a course for R users who want to get more out of R. Knowledge of R is a prerequisite, and Presciient’s course “Introduction to R and Data Visualisation” is an ideal first step, along with work or project experience in using R. Attendees should be able to write R programs including loops, conditionality, scripts, and functions. They should also be familiar with the most basic data types: vectors, lists, matrices, and data frames, and means to index and manipulate them.
The course will be led by Presciient director, Dr Eugene Dubossarsky. He is the head of the Sydney Users of R Forum. Eugene is also Principal Founder of Analyst First, an international analytics industry organisation. He is a founder of the Institute of Analytics Professionals of Australia (IAPA); Director, University of New South Wales School of Mathematics and Statistics Industry Advisory Board; and a recognised industry leader in business analytics. Eugene is an experienced analytics professional with 20 years’ experience programming in R and its parent language, S.
The Introduction to R course provided clear and logical assistance to getting up and running with R. More than that, the real value was in providing guidance on the myriad of online resources and introducing me to a network of passionate and helpful R users. Eugene is a knowledgeable and approachable teacher. I wouldn’t hesitate in recommending the course. I feel that I am now fully on the road to applying R and using data to improve efficiency across my organisation.
—James Orton, Data and IT Manager, UNICEF Australia
I have been trying to convert my Stata programming skills to R, however, there have been many times where I just wanted to sit down with someone and have them explain the fundamentals of programming in R. Sure, a number of books and websites have helped me become familiar with R, however, I still didn’t feel ready to translate all of my familiar Stata commands to R (e.g. I am comfortable plotting graphics using ggplot2, however, revert back to Stata for data manipulation). I knew that a more effective way to learn and feel confident would be to sit down with someone and have them explain how they use R, how they clean data, how they plot graphics, etc. I knew that once I felt comfortable with cleaning my data in R, analysis would be less of an issue—I’m happy to research the specifics on my own.
Thank you Eugene for advancing my R skills. I especially appreciate the time spent explaining the fundamentals of data manipulation — i.e. the code one needs to know before running any basic or sophisticated analysis. The pace of the workshop was perfect.
—Dr Chelsea Wise, Lecturer, Marketing, UTS Business School
The course assumes no tertiary level training in statistics. Attendees simply need to be familiar with working with structured, electronic data.
Please ask about our discounts for group bookings.
Use email@example.com to email us any questions about the course, including requests for more detail, specific content you would like to see covered, or queries regarding prerequisites and suitability. If you would like to attend but for any reason cannot, please also let us know.
Course material may vary from what is advertised due to the demands and learning pace of attendees. Additional material may be presented along with or in place of what is advertised.
The course may be cancelled by the organisers with full refund of fees.