This course will introduce students to the principles and best practices of programming reproducibly for biological data analysis, prediction, and validation.

This course will consist of 13 sessions last 4-5 hours each, supplemented with additional help sessions. You are expected to devote a total of ~200 hours for a 20-credit course (including contact hours and formative work outside of class).

None

The course is divided into four thematic series, each capped by an assessment of the practical work initiated in class. For each assessment, students will write and submit annotated scripts and reports generated in R, reflecting participation and competencies learned in practical computer laboratories (50%, i.e. 12.5% each). The remaining 50% will be based on a final independent assignment studied during last day of class and completed after the course that will require integration of the evidence-based knowledge and skills learned, involving direct application of programming skills drawn from 4 main themes.

No reassessment opportunities are available for the small assignments done during the course, as solutions will be discussed in class.

Students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

Practicals cannot be reassessed.

The aim of this course is to provide hands-on training in programming techniques; to write comprehensible and reproducible programmes that can be understood by other people who examine it; and to apply those skills to advanced data analysis.

With reference to the evidence base, by the end of this course students will be able to:

■ Use appropriate data structures to retrieve and store information

■ Select and justify the appropriate program structures when solving a problem

■ Use comments appropriately to explain program structure and design

■ Write and document functions to carry out specific procedures

■ Design simple computer programs to solve specified problems

■ Generate reports in R where code is run, and the output is discussed

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.