In all aspects of modern quantitative research, there is a need for competency in the application of computational data analysis techniques. The R language and environment provides the means to manipulate, integrate, and interrogate data. R includes a wide variety of statistical, machine learning, as well as data visualisation packages, and is one of the most widely used programming languages for the sciences. This course is specifically designed for and targeted at those with no prior computational background or experience, who wish to enhance their data analysis skillset.

Learning will draw on real-world examples, with an emphasis on those from biological, health, medical, and social sciences. The course will provide coding expertise in a computer laboratory environment delivered by in-person teaching, feedback, and positive reinforcement of good coding practices. 

The course will run over two weeks. The first week will be held in-person, in a computer lab on the Manor Park, University of Surrey campus. The structure for this first week will follow a format of an initial face-to-face lecture for each topic to introduce key concepts and examples, followed by interactive workshops to apply these concepts using the R coding language. Subsequently, students will spend one week completing a code-based project and submit this for assessment. Students may choose to carry out the project on their own data, or they may select from a number of available datasets and topics. Additional learning materials will be provided ahead of the course, as well as following the face-to-face week, for independent study. 

Please note that although there are no specific entry requirements, participants should have an undersgraduate degree, ideally from a Sciences, engineering, health/medicine/dentistry background.

Our Terms and condition, as well as more information on the course, are available from our webpage.