INF2-FDS: Workshops
Purpose of the workshops
The FDS workshops are a crucial part of the course. They should help you to develop your understanding of ethics, visualisation, critical evaluation of case studies and statistical problems.
The principle of the workshops is that you learn actively by discussing and working with others in a group. As the late Informatics Professor Jon Oberlander said: "Conversation makes you smart". You will benefit most by undertaking the assigned task (see below) before the workshop, but even if you have not done the task, we encourage you to attend, as you will learn either by doing the task in the workshop, or from other students who have managed to do more.
Two of the workshops are designed to give you an understanding of how we will assess the courseworks that follow, and the workshops on statistical literacy should help with the class test.
Workshop logistics
Workshops will be held in weeks 3, 5, and 9 of Semester 1 and weeks 2, 4, 6 and 9/10 of Semester 2. In the week before the workshop we will usually give you a task to prepare for the workshop, e.g. reading or doing some exercises. You will find the task in that week's folder in Course Materials and linked from the Schedule.
Each workshop group has up to 40 students and 2 tutors. During the workshop, you'll be expected to work together in smaller groups around tables. The location and time of your workshop group is in your personal timetable.
Each table has its own monitor, and it's often helpful to have one member of the group sharing their laptop screen on the monitor. There are HDMI and VGA connectors to the monitor, but not other connectors. So, if you can, please bring a laptop and HDMI dongle with you to the workshop.
Changing your workshop group
If you want to change your on-campus workshop group, please fill in the Group change request form. You can indicate your preferred option for a group change when you fill in the form (there is also a comment section where you can give further details).
List of workshops
- S1 Week 3: Ethical discussion
- S1 Week 5: Visualisation
- S1 Week 9: Linear Regression and critical evaluation
- S2 Week 2: Data science readings
- S2 Week 4: Statistical problems 1
- S2 Week 6: Statistical problems 2