2  Schedule

The course is structured as a series of participatory live-coding sessions interspersed with hands-on exercises and group work, using either a practice dataset or some other real-world dataset. There are some lectures given, mainly at the start and end of the course. The general schedule outline is shown in the below table. This is not a fixed schedule of the timings of each session—some may be shorter and others may be longer. Instead, it is meant to be an approximate guide and overview.

Time Session topic
9:30 Arrival; Coffee and light breakfast
10:00 Introduction to the course
10:30 Setting up an R project (with short break)
12:20 End of session short survey
12:30 Lunch
13:15 Networking and social activity
13:35 Analytically reproducible documents
14:40 End of session short survey
14:45 Break with coffee and snacks
15:00 Version control with Git
16:30 End of session short survey
Time Session topic
9:00 Importing data into R
10:10 End of session short survey
10:15 Break with coffee, team and snacks
10:30 Basic data visualization (with short break)
12:20 End of session short survey
12:30 Lunch
13:15 Networking and social activity
13:35 Collaborating with GitHub
14:40 End of session short survey
14:45 Break with coffee and snacks
15:00 Basic data wrangling
16:30 End of session short survey
Time Session topic
9:00 Wrangling with visualizing
10:10 End of session short survey
10:15 Break with coffee and snacks
10:30 Split, apply, and combine
12:20 End of session short survey
12:30 Lunch
13:15 Group work (with break)
16:00 Testing reproducibility of projects
16:10 Closing remarks
16:30 End of course short survey and farewell