Introduction to R programming

Course Dates: 30/10/21 - 20/11/21
Time: 10:00 - 13:15
Location: Online
Programming is the cornerstone of keeping up with business and technology. Learn the immensely popular language R to boost your skills and widen your horizons.
This course is FREE if a) you live in London and your job is at risk of redundancy or b) you are either on Jobseekers' Allowance (JSA) or Employment & Support Allowance(ESA) or c) you receive other state benefits (including Universal Credit) and your monthly take home pay is less than £343. For more information click here
This course will be delivered online. See the ‘What is the course about?’ section in course details for more information.
Book your place
In stock
Full fee £199.00 Senior fee £159.00 Concession £100.00

Course Code: CRC02

Sat, day, 30 Oct - 20 Nov '21

Duration: 4 sessions (over 4 weeks)

Or call to enrol:020 7831 7831

Any questions?
or call 020 7492 2515

Please note: We offer a wide variety of financial support to make courses affordable. Just visit our online Help Center for more information on a range of topics including fees, online learning and FAQs.

What is the course about?

R is a programming language used widely for statistics, machine learning and data mining. Its popularity has increased a lot in recent years, and it is particularly useful for business and science. This course is designed for those who have little to no programming experience, and would like to learn a computational way of thinking as well as a very useful language. If you have experience in another language and would like to pick up R, you will be provided with extra material suited to your level.

This is a live online course. You will need:
- Internet connection. The classes work best with Chrome.
- A computer with microphone and camera.
- Earphones/headphones/speakers.
We will contact you with joining instructions before your course starts.

What will we cover?

For the first half of the course we will cover the basics of writing code in R. This will include concepts like data types, operators, lists, variables, data frames, functions, loops, and importing data.
For the second half we will move on to how this can be applied. We will have a look at how to use R for statistics, graphics, data mining, machine learning and time series. To make it more interesting, we will use real life examples from science, finance, and everyday life.

What will I achieve?
By the end of this course you should be able to...

Solve simple problems using R programming. This could include analysing business data, or using data frames for handling large data sets. Being a good programmer is all about experience, but this course will give you the skill set to tackle new problems on your own. You will learn how to handle syntax errors and what to do when you get stuck.

What level is the course and do I need any particular skills?

The course is introductory, and no programming experience is required. Basic computer skills are required.

How will I be taught, and will there be any work outside the class?

You will be introduced to a topic, then you'll try programming it. There will also be exercises and games so you're not sat still staring at the screen all day. There will be optional, but highly recommended homework set.

Are there any other costs? Is there anything I need to bring?

There are no additional costs.

When I've finished, what course can I do next?

Introduction to machine learning, Introduction to Python. You might want to explore the Excel courses in data analysis such as: Data analysis with Power BI, Excel analysing data (stage 1 & 2) Introduction to DAX: data analysis expression for Power BI.

Liv Helen Vage

Liv is a physicist with background in machine learning. She completed her masters degree at University College London, with a thesis in theoretical astrophysics, and is currently working on a PhD in particle physics at Imperial College. She first started exploring machine learning at the Wolfram Summer School in Boston, and has since done internships with BT in the UK and DESY in Germany. Her PhD centrers around using novel methods for high performance computing and machine learning for the upgrade of the compact muon solenoid experiment at CERN in Switzerland.

Please note: We reserve the right to change our tutors from those advertised. This happens rarely, but if it does, we are unable to refund fees due to this. Our tutors may have different teaching styles; however we guarantee a consistent quality of teaching in all our courses.