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.
- Speed up their R application.
- Make use of wider memory stores.
The course will introduce attendees 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
- String processing with package stringr.
- Date processing with package lubridate.
- SQL in R with sqldf.
- Data processing and transformation with packages plyr and reshap2.
- Efficient data processing and transformation with newly released packagedplyr.
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
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.
Windows PCs 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.
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.
Please ask about our discounts for group bookings.
I found the Introduction to R course extremely helpful. I have had very limited experience with R (and programming / statistical computing in general) and I now feel confident that I can use the language to do what I need with my data. The course was well designed and the notes are very helpful. I recommend this course to anyone who is new to R and wants to learn quickly.
- Helen McCormick, PhD student, Epigenetics Laboratory, Victor Chang Cardiac Research Institute
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