Business Booking Details

Payment Of Invoices

For bookings from established businesses, we do not require payment at the point of booking.

We will send you an invoice which you can submit to your accounts payable system.

Purchase Orders

If your employer uses a purchase order (P.O.) system to manage supplier invoices that is no problem.

  • If you already have a P.O. number when booking add it to the PO number box on the booking form, and we will include it on your invoice.
  • If you need an invoice to generate a P.O. number in your accounts system, please book the course as normal and add a note in the PO number box – to be provided
  • We will send you an invoice (without a P.O.) which you can use to generate a P.O..
  • We will then re-issue your invoice with your P.O. included when you provide us with it


You are not able to pay directly online at the time of booking, we issue an invoice for all bookings.

We accept payment either via direct bank transfer or card

Our invoices contain our bank details if you would like to pay by bank transfer and there is also information on how to pay by card.

Please note, if you are using a business card there is a surcharge of 2% to cover the payment processing charges.

This advanced R training course will introduce you to the more powerful functionality of R.

Our highly experienced R trainers will have plenty of time to answer your questions due to our small class sizes. Our courses are hands-on, meaning you will gain vital practical experience.

What Will I Learn?

You will learn more advanced ways to manage data items, such as working with incomplete data and merging datasets. You will also learn some methods of supervised machine learning for data analysis.

These topics include linear and curvilinear regression, non-gaussian regression and model-building. You will learn how to customise the powerful graphical capabilities of R to produce visualisations of your data and results.

You’ll see how to use R to produce custom solutions for your data. You will learn a range of programming techniques, which include loops, conditional statements, error trapping and creating custom classes for your own summary and plot routines.

By the end of this course you will be able to:

  • Import data (data munging).
  • Work with and manipulate data objects.
  • Work with data tables.
  • Carry out cross tabulation.
  • Gather summary data from tables.
  • Visualise your results.
  • Create custom solutions.

Am I Ready For This Course?

This training course assumes a basic working knowledge of using R, and builds on the Introduction course.

The Training Day

Our courses run from 9.30am to roughly 4.15pm with refreshments throughout the day and a break for lunch.

We offer a relaxed, supportive learning environment, fully air-conditioned training facilities and some of the nicest instructors on the planet.

Also, you’ll receive:

✔ A full-colour manual which covers everything in the course.
✔ Your course exercises so that you can practice at home.
✔ A Certificate of Attendance.


The session starts with a brief look at importing data items and builds on the beginners’ course by showing some advanced methods for data import and validation, including how to read Excel files

  • Making data items
  • Factor variables

In this session you will learn how to explore and alter object properties. You’ll also learn how to make data objects and to merge datasets.

  • Joining – cbind, rbind merge

In this session you’ll learn more advanced methods for summarizing data tables:

  • Data summaries
  • apply()
  • tapply()
  • sapply()
  • aggregate()
  • prop.table()
  • addmargins()

Advanced graphical methods
In this section you will learn more advanced methods of graphical summary. Topics include: error bars, using colour palettes and making legends. You’ll also learn how to alter graphical parameters to produce more customised plots, as well as methods for adding items to plots (such as labels, additional text and more data series).

  • Error bars
  • Legends
  • Colour
  • Labels
  • Adding to plots
  • Graphical parameters

This section of the course covers various aspects of regression analysis, including: model-building, non-gaussian regression, curvilinear regression, best-fit lines (straight and curved).

This section of the course covers both the basics of R programming and a few more advanced areas to give you a complete overview of the methods you’ll need to produce custom solutions. Topics include: loops, conditional statements, invisible results, user intervention, error trapping, and argument matching.
You will learn how to use custom classes for producing your own print, summary and plot routines. You will also learn how to save and load custom functions and scripts.

  • Basic methods
  • Custom classes and other advanced methods

Online Training Requirements

To attend this R course online, you will need:

R on your Windows PC/laptop with a camera, speakers & microphone
A stable internet connection capable of running Zoom
To be a confident computer user and able to use Zoom

If you have access to a second screen, we would encourage you to use it as it improves the experience.