R is the most popular data mining and statistics package in the world, and it is free to use. It is also easy to use thanks to a range of intuitive graphical user interfaces for statistics, data mining, and interactive visualisation. It is used by a growing number of commercial and government organisations, and is also the tool of choice of elite data mining competition winners. R is open source, flexible, and customisable. Over 10,,000 R packages are available as extensions to the base environment, constituting one of the largest and most up-to-date collections of cutting edge Analytics tools in the world. It is also one of the most visually spectacular and universally applicable data visualisation tools.
This two-day course is an introduction to the R programming language, beginning with the most basic operations of downloading and installing the environment. Participants will learn how to input and manipulate data and be instructed in all the aspects of procedural programming in R, allowing them to create their own R functions and customise code. The course will also introduce R data structures, statistical operations, the creation of R visualisations, and options for generating output from all of these to external files. It will also provide an overview of the use of packages in R, and an introduction to some of the most common data mining, interactive visualisation and integrated graphical user interface packages.
Face to face public courses: early bird pricing is available until 2 weeks prior. Group discounts: 5% for 2–4 people, 10% for 5–6 people, 15% for 7–8 people, and 20% for 9 or more people. Discounts are calculated during checkout.
Online public courses: available at a 25% off the face-to-face courses as a special introductory price. to groups or to individuals who want to follow a curriculum program and attend multiple courses:
- 2-4 courses/attendees 10% off
- 5+ courses/attendees 20% off
Hurry as bookings will close 1 week before each course. Group discounts are calculated during checkout on individual courses. Individuals can book multiple courses at a discount via the Curricula booking page.
This is a practical course, suitable for existing and prospective data-analysis practitioners in government and industry. Participants will be provided with a range of programmatic and user-interface options for working with data in R. The course assumes no specialised statistical knowledge. Its focus is developing a practical understanding of R as a tool for business users.
|Pre-requisites||The course assumes no tertiary level training in statistics. Attendees need to be familiar with working with structured, electronic data and should have completed or have equivalent knowledge to the courses Critical Thinking for Data Analytics and Data Literacy for Everyone|
|Objective||Attendees will, by the end of the course, have the basic skills, resources, guidance and confidence to immediately and self-sufficiently begin to use R in their work.|
|Course Author||Dr Eugene Dubossarsky|
|Trainer||Courses are taught by Dr Eugene Dubossarsky and/or his hand-picked team of highly skilled instructors.|
|Delivery Method||In-person at AlphaZetta Academy locations or on-premise for corporate groups|
Our online courses run as live online meetings using Zoom for the video meeting part and Microsoft virtual computers for the practical components. The benefit of having a live trainer for online training is you can ask questions, obtain mentoring from the trainer and interact with classmates.
Course participants will require the following technologies and online accounts. Please check that your setup satisfies these requirements:
- Course participants will require the following technologies and online accounts:
- Reliable computer (Windows, Mac or Linux)
- Webcam (to help facilitate the mentoring aspect of our training)
- Reliable internet access
- A quiet space
- Zoom video conferencing software and Zoom account (register and pre-install the software at zoom.us)
- Microsoft account in order to access the virtual lab PCs (Existing or new account. There’s nothing to be installed, you just need an account to sign-in with.)
Meals and refreshments
Face-to-face courses: Catered morning tea and lunch are provided on both days of the course. Please notify us at least a week ahead if you have any special dietary requirements.
Use firstname.lastname@example.org to email us any questions about the course, including requests for more detail, or for 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 advertised due to demands and learning pace of attendees. Additional material may be presented, along with or in place of advertised.
Cancellations and refunds
You can get a full refund if you cancel 14 days or more before the course starts. No refunds will be issued for cancellations made less than 14 days before the course starts.
Frequently asked questions (FAQ)
Do I need to bring my own computer?
This is dependent on the venue. Please check the course event page.
Why do I need to provide a shipping address?
For online courses, we need an address to send you the course notes that you need for the course.
Private and Corporate Training
In addition to our public seminars, workshops and courses, AlphaZetta Academy can provide this training for your organisation in a private setting at your location or ours, or online. Please enquire to discuss your needs.
Scheduled Public Courses
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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.
For someone who does not come from an IT background R is a terrifying program. Before doing the Introduction to R course I had previously done other courses in R but always found myself in over my head because they assumed a high level of program experience (even course that required no prior programming knowledge). This course is not like that at all. It starts at ground zero and teaches you everything you need to know to be able to use R confidently in your everyday workplace. It is a must attend for anyone who wants use R!
I have been very fortunate to be on the R & Data Visualisation course read by Dr. Eugene Dubossarky.
I was thinking of doing computational finance with R—data analysis, statistical modeling, and data visualization for large financial datasets, e.g. quantifying market risk measures—without the heavy lifting in Excel. And I was looking for the most effective introduction to programming in R.
The course exceeded all my expectations, given the breadth and quality of the information provided in Dr. Dubossarky’s presentation. The pace and structure of the course made learning intuitive and comfortable; providing cross-references between different programming languages and R showed the language capability in a familiar way; the elegance and power of R, its ability to facilitate rapid data analysis and visualisation were demonstrated in a number of real-life examples—encouraging us to integrate the course materials into our day-to-day tasks, and continue learning.
What I found also invaluable was his recommendations for numerous online resources, as well as offering his post-course support. All in all, this was the best start I was hoping for. I’d be happy to recommend this course for any corporate environment either in transition or thinking of switching to R.
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.