At KUB Datalab we use and support a large array of software.
We have tried to organise our main tools into categories below. Bear in mind, that many types of software can be used for multiple purposes. We have tried to categorise by main purpose.
At KUB Datalab we facilitate different course types and methods for working with software and tools.
We offer courses in data processing, annual data sprints and workshops for students and researchers that you can read more about on this page.
The Datasprints are tightly facilitated. This means that the structure is outlined from the beginning, and the tasks, instructions, software, and data sets are carefully selected.
The participants will be introduced to a determined topic, the determined tasks, and the software and the data sets they much use to to solve the tasks. The organizers are responsible for these introductions to make sure the participants are fully equipped to overcome the challenges they will meet throughout the Datasprint.
Once the Datasprint has begun, it is up to the participants to solve as much of their tasks they can. The organizers are present throughout to offer any guidance the participants may need. Once the time is up – and all participants have crossed the finish line – hopefully they have learned a whole lot more about the topic, software, data, and digital methods.
You can sign up for our open courses through the calendar. The content of some of the courses is aimed at subjects at for instance the humanities or science, and you may also sign up for those courses if you are interested in cross-curricular work. Other courses are aimed at several subjects. Some of the courses feature a practical intake to learning and emphasize active participation and exercises while others access learning analytically.
Participation on most courses does not imply prior knowledge of the programs we teach. These are often elementary courses which ought to inspire participants to either attend again and participate in a new course, or inspire the participants to explore the programs further on their own. Few courses assume previous knowledge and it will appear from the course description.
We want to create a safe, curious, and including learning environment where it feels natural to ask questions and in which errors and uncertainty will not be associated with shame, but form a natural part of the process of learning something new. It is important for us that both teachers and participants take responsibility for creating an including learning environment, and that we all use an including and appreciative language and acknowledge other people’s experiences and points of view.
Write to us if you have questions for the courses.
The KUB Datalab open workshops are an opportunity for drop-in assistance. Students (and others) can drop by with their own data and specific problems, large or small. The KUB Datalab team will then do their best to assist in solving the problem. The approach chosen depends on the specific task, but is usually explorative and based on dialogue. Questions of a more specific statistical nature, eg which test to apply in a given situation, or that require software development, are usually referred to similar labs at Copenhagen University. As default the open workshops support all software in the portfolio of the lab, but we are not able to guarantee that colleagues with the necessary knowledge are available at all times.
The Carpentries is a global network of instructors, organisations and others, teaching foundational coding and data science skills. Workshops organized under the auspices of The Carpentries are collaboratively developed and founded in evidence based teaching practices. KUB Datalab offers the full collection of Carpentries branded workshops presented at https://carpentries.org/, as well as individually tailored workshops.
