R Course Coordinator: Matthew Exact
Arrangements: The course will be held every Wednesday in Term 2
Sign ups: Registration will be available at the end of Term 1
Aims: This course offers a comprehensive and in-depth overview of the main aspects of the R language. This series of seminars and lab lectures are intended to provide the student with research-related tools, and examples of topics in computational statistics. All in all, this course will provide students with a strong background in R programming which will be beneficial when:
(a) taking academic modules that use R to illustrate practical applications
(b) embarking on a data analysis career.
Objectives: At the end of this course, students should have a broad understanding of the R language, and the ability to write concise code that can be used across many areas of data analysis. Specifically, students ought to be familiar with:
(a) R data types and the best way to perform operation on them
(b) functional programming and its role in data analysis and processing
(c) basic algorithm design.
Content from Marco’s course (2016/17):
- Lab lectures:
- Tidy data sets.
- A Sneak Peek into Machine Learning: Support Vector Machines
- The wonders of “foreach:” the joy and pain of parallel programming in R.
- Web Scraping in R.
- Reproducible Research: why it matters and how to do it.