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Build on your existing R skills and learn to run analyses more efficiently. In this advanced-level course, you’ll explore multiple approaches to problem-solving in R, focusing on creating your own functions, using control structures, loops, and functional programming techniques. You’ll also learn how to streamline your code using tidyverse piping syntax and create advanced visualisations with ggplot2.
Led by our Data Analytics Lead, Tamara Shatar, this hands-on course includes guided exercises to reinforce each concept and help you build practical, reusable solutions in R.
By the end of this course, participants will be able to:
Completion of R Beginner and Intermediate courses or basic R familiarity is recommended. You should also have a basic understanding of statistics such as mean, median, and standard deviation.
Select your country to view prices, and course dates.
R BeginnerLearn the basic principles of R programming, the language for statistical and data analysis.
R IntermediateData manipulation, basic exploratory data analysis, customised data visualisations and basic modelling in R.
Machine Learning in RLearn the basic processes of machine learning using R programming. Led by an experienced data scientist.
Working more efficiently in R
How to work more efficiently in R
Vectorisation
Using better functions
Concise code
Reusable scripts
Custom functions
Loops and other control structures
Loop alternatives
Functions to reduce typing
Printing objects after creating
with and within
Inserting multiple quotation marks
Create your own functions
Why write your own functions?
Basics of functions
What is a function?
Creating your own functions
Syntax for writing your own function
More complex functions
Ellipses and further arguments
Scope
Loading your functions
Loops and control structures in R
If and if else
Loops for loops
Saving results from a loop
Improving your code
While loops
Repeat loops
Loop alternatives
Functionals
apply functions
split
map functions
map variants
Returning a vector
walk
Loop, apply or map?
Tidyverse piping syntax
Purpose
Using the pipe
Pipe variants
The tee operator
The exposition operator
Plotting with ggplot2
The grammar of graphics
Required components
Using ggplot()
Scatterplot
Line chart
ggplot2 resources
Course Introduction
Our R courses were designed by Tamara Shatar, who holds a PhD in Agricultural Data Science. She focused her extensive experience and skills in modelling using machine learning, simulation and other techniques to create a course with depth and applicability.
The course is consistently well reviewed by students.
"The course was really good, the resources provided to help after the course are excellent. I was a bit overwhelmed at the beginning trying to learn a new language, but I was put at ease and we went through the content at a pace that I could understand." - R Beginner Brisbane
"Interesting material and very well run. Thanks again." - R Advanced Brisbane Remote
What is Remote Training?
We offer some of our more specialist courses in a remote format. At Nexacu, this means you will learn the same content as you would in our classrooms and the same trainer will deliver training but all students will log in from their own premises and device. Our Data Scientist, Tamara will host the Data Analytics training sessions, walking you through the basics of R and answering questions and encouraging discussion along the way.
Why Learn R?
Rather than being a point-and-click tool, R is a language that is used for writing reusable scripts, enabling automation and repeatable workflows. Because it is a language, it offers a huge amount of flexibility in manipulating data and the ability to write new functions. Even without a background in programming, it is relatively easy to get up and running once you know the basics.
R BeginnerLearn the basic principles of R programming, the language for statistical and data analysis.
R IntermediateData manipulation, basic exploratory data analysis, customised data visualisations and basic modelling in R.
Machine Learning in RLearn the basic processes of machine learning using R programming. Led by an experienced data scientist.
At Nexacu, we are proud to be the trusted training partner for hundreds of leading organisations across Australia, New Zealand, and around the world. From government agencies to multinational corporations, we help teams build practical skills and achieve real outcomes through expert-led training.
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Custom workbook included with a step by step exercises
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