AlphaZetta Academy

Advanced R 2

This course goes deeper into the tidyverse family of packages, with a focus on advanced data handling, as well as advanced data structures such as list columns in tibbles, and their application to model management. Another key topic is advanced functional programming with the purrr package, and advanced use of the pipe operator. Optional topics may include dplyr on databases, and use of rmarkdown and Rstudio notebooks.

See what former trainees are saying about our R courses.

Additional Information

Audience Expert
This is a practical course, suitable for existing data-analysis practitioners in government and industry.
Prerequisites Students should have completed or have equivalent knowledge to the courses Intro to R (+data visualisation) and Advanced R 1
Objective The objective of this course is to give the data scientist the power of the tidyverse for data manipulation and functional programming: this results in code that is easier to read, revise and share, as well as much faster to write and more bug-free. These skills are also vital for rapid, scaled development of predictive models and other data analytics.
Format Class
Duration 2 days
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.

Meals and refreshments

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.

Feedback

Use academy@alphazetta.ai 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.

Variation

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?

There’s no need to bring your own laptop or PC. Our courses take place in modern, professional training facilities that have all the computing equipment you’ll need.

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. Please enquire to discuss your needs.

Enquire Now

Scheduled Public Courses – BOOK NOW!

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. Please enquire to discuss your needs.

Enquire Now

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Testimonials

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!

Alix Duncan

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.

Elena Nazvanova

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.