Since the last review in 2018, not much has changed. The TL;DR: AVOID THIS UNIT(!!!!!). R is the second-most popular scientific programming language, and almost all statistical analyses in the life & environmental sciences that can be run on a local computer are run in R(Studio). BUT, don't think having some/any programming experience will help you: In this unit, you'll be pushed to use their own copy-and-pasted, clunky R-base code. Coding your own way, even if you reach the same answer, will NOT be marked. This seems to all be in spite of the step changes over the last decade in R scientific programming practices--including way more efficient C# implementations of the statistical & numerical models taught in the unit, code/statistical reproducibility (e.g., this unit doesn't teach 'set.seed()'), and transparent use of AI. In an increasingly uncertain & changing climate and environment, there's simply no place for quarter-of-a-century-old code on old case-studies and resistance to change and new case-studies. There's a recent Conference Abstract online that preaches the teaching successes of this unit--I don't buy it. My advice: take other units if you're after 1) more up-to-date R scientific programming skills and 2) a safe/accomodating/encouraging space for solving environmental & earth science problems

This unit was disorganised and difficult. The lecturers don't talk to one another and aren't overly helpful. The unit does not require maths or coding experience in theory, but without some, you're totally lost. The computer lab demonstraters can be hit or miss, some are fantastic but some refuse to help you or can't help you because the program used (r-studio) is not generally used by scientists in the field.