M10-Mastering R Skills: Selected Topics for Successful Programming

Description

R is a powerful and extensive language, and in recent years a lot of useful additions have been made. This also makes it confusing at times to link the different paradigms together and find the most optimal workflow.

This course is aimed at giving you more insight in how to work more efficiently with R and RStudio. We focus on some more challenging data types, and give an overview of the necessary building tools to optimize your workflow.

The following topics will be covered:

• Working with text: text comparison and editing with help of regular expressions
• Working with dates and times
• Working with files, folders and projects to organise your work
• Automating using functions for standard R, tidyverse and ggplot2

Fees and registration

Fees and registration form are available on the website of the Academy for Lifelong Learning of the Faculty of Sciences (UGent).

Target audience

This course is aimed at R users with previous experience who want to optimize their workflow. The tools offered are useful both in research and in more commercial applications.

Course prerequisites

Participants need previous experience with R and RStudio. They should have a good insight in how to work with vectors, matrices, data frames and lists. They also need to have a good basic understanding of the tidyverse data wrangling packages (dplyr and tidyr) and ggplot2. The topics covered in Module 1, Module 7 and Module 8 of this year's program are considered as known.

Exam / Certificate

There is no exam connected to this module. If you attend all four classes you will receive a certificate of attendance via e-mail at the end of the course.

Type of course

This is an on campus course. We offer blended learning options if, exceptionally, you can't attend on campus in person.

Schedule

Four evenings during the Easter Holiday: April 3, 6, 11 and 13, 2023, from 5.30 pm tot 9 pm.

Venue

Faculty of Science, Campus Sterre, Krijgslaan 281, building S9, 9000 Gent

Course material

• Exercises and slides provided by the instructor
• Cheat sheets and online manuals provided by the instructor

Click here to see the overview of all modules in this year's course in Data Analysis