R Programming for Data Science: Introduction



Overview

R is a popular and free programming language. It is easy to install and works on common platforms such as Windows, Linux and Mac. Even if you have limited or no computer programming experience, R is easy to learn.

Its applications span various areas such as statistical significance testing, data analysis and visualisations, data processing, manipulation and summarisation. An example is the fact that it is fairly easy to perform MS Excel, or SQL-like operations with R. In addition, R is a good choice for machine/deep learning, image analysis and processing and much more.

During the course you will learn the basics of the popular R programming language and how to use it to manipulate data and perform excel-like operations. 

This course begins with the very basics of R and its syntax and control statements, and gradually builds up to cover lots of useful functionalities and data manipulation. For example, the course covers control statements and instructions related to decision making and iterations as well as various types of data structures and functions. After this, you will learn how to use R to apply several common data processing and manipulation operations.

The course is designed in such a way that people with minimal or no computer programming experience can use it as a foundation to learn more advanced R topics or transfer their skills to other programming languages.

This is an in-person course which takes place in Oxford. The course will also run online in January 2026 and April 2026.

Programme details

Course starts Tuesday 30 September 2025

This is an in-person course which requires your attendance at the weekly meetings in Oxford on Tuesdays, 7-9pm.

  • Week 1 (30 Sept): R Introduction (includes R installation): R Reserved Words, Variables & Constants, R Operators and Operator Precedence.
  • Week 2 (7 Oct): Decision and Loop: if…else, for loop, while loop, break & next
  • Week 3 (14 Oct): Functions: What are they? How to write your own Function, Function Return Value, Environment & Scope.
  • Week 4 (21 Oct): Data Structures - Part 1: Vectors, Matrices and Lists.

Tuesday 28 October: there will be no class this week

  • Week 5 (4 Nov): Data Structures - Part 2: Data Frames and Factors. Slicing, Selection and Filtering.
  • Week 6 (11 Nov): Basic Graphs & Charts: Bar Plot, Histogram, Pie Chart, Box Plot (includes when to use them and how to interpret them).
  • Week 7 (18 Nov): File Reading and Writing: How to read from and save to text files, CSV files and Excel sheets.
  • Week 8 (25 Nov): Data Manipulation - Part 1: Dealing with Missing and Duplicate Values, Sorting and Data Type Conversion.
  • Week 9 (2 Dec): Data Manipulation - Part 2: Merging and Joining Data Frames
  • Week 10 (9 Dec): Data Manipulation - Part 3: GroupBy and Pivot Tables. Working with Date/Time Data.

Certification

Academic credit

Credit Accumulation Transfer Scheme (CATS Points)

Please note, students who do not register for assessment and accreditation during the enrolment process will not be able to do so after the course has begun. If you wish to gain credit from completing this course you must register to do so before the course starts.

Only those who have registered for assessment and accreditation will be awarded CATS points for completing work to the required standard. Please note that assignments are not graded but are marked either pass or fail.

Learn more about the Credit Accumulation Transfer Scheme.

If you are enrolled on the Certificate of Higher Education at the Department you need to indicate this on the enrolment form but there is no additional registration fee for assessment and accreditation.

Digital certificate of completion 

Students who are registered for assessment and accreditation and pass their final assignment will also be eligible for a digital Certificate of Completion. Information on how to access the digital certificate will be emailed to you after the end of the course. The certificate will show your name, the course title and the dates of the course attended. You will be able to download the certificate and share it on social media if you choose to do so.

Fees

Description Costs
Course fee (with no assessment) £300.00
Assessment and Accreditation fee £60.00

Funding

If you are in receipt of a UK state benefit, you are a full-time student in the UK or a student on a low income, you may be eligible for a reduction of 50% of tuition fees. See details of our concessionary fees for short courses.

Tutor

Dr Gisela Robles Aguilar

Gisela is Senior researcher in Global Burden of Disease at the Nuffield Department of Medicine, University of Oxford, where she applies different machine learning models to understand infections that are resistant to antibiotics and to inform public action on health outcomes and inequalities. She has been a tutor for the Social and Medical Sciences Divisions within the University of Oxford, and also has been a Fellow of the Higher Education Academy (FHEA) since 2017. She also contributes to disseminating analytical methods to decision makers, focusing on resource-limited settings.

Course aims

An introductory overview of the R programming language is covered in this course. Students will be shown the basics of R and move on gradually to data processing and performing excel-like operations on tabular data.

Course objectives

  • To introduce programming with R.
  • To introduce how to read data from files.
  • To introduce how to perform excel-like operations with R.

Learning outcomes

Students will have been given the opportunity to have learnt how to...

By the end of the course:

  • understand R syntax, basic control flow and program design;
  • understand R data structures and how/when to use them;
  • understand how to perform Excel-like operations with R.

After attending the course:

  • foundational programming concepts such as variables, iterative statements, conditionals, functions and data structures;
  • how to read and write files, how to generate basic plots and visualisations and how/when to use data structures;
  • how to perform several excel-like operations such as sorting and filtering data, joining tables and much more.

Assessment methods

Only those students who have registered for assessment and accreditation, in advance of the course start date, can submit coursework/assignments for assessment.

Assessment

The assessment will be a set of ten questions that will enable students to demonstrate an understanding of the material discussed during each week of the course.

Please note that summative assignments are not graded but are marked either pass or fail. 

Application

How to enrol

Please use the 'Book now' button on this page. Alternatively, please complete an enrolment form.

How to register for accreditation and assessment

To be able to submit coursework and to earn credit (CATS points) for this course, if you wish to do so, you will need to register and pay an additional £60 fee. You can do this by ticking the relevant box at the bottom of the enrolment form or when enrolling online. 

Students who do not register for CATS points during the enrolment process will not be able to do so after the course has begun.

If you are enrolled on the Certificate of Higher Education at the Department you need to indicate this on the enrolment form but there is no additional registration fee.

Level and demands

The Department's Weekly Classes are taught at FHEQ Level 4, ie first year undergraduate level, and you will be expected to engage in a significant amount of private study in preparation for the classes. This may take the form, for instance, of reading and analysing set texts, responding to questions or tasks, or preparing work to present in class.

Terms & conditions for applicants and students

Information on financial support