Currently teaching

I am currently teaching the following courses in collaboration with colleagues:

• Introduction to digital humanities and to the digital treatment of language data (2024) at the PhD school from the University of Copenhagen, together with four colleagues
• Language Processing I (2017-) at the M.S. in IT & Cognition (University of Copenhagen), together with a colleague
• Language Processing II (2017-) at the M.S. in IT & Cognition (University of Copenhagen), together with a colleague
• Language Technologies for Digital Humanities (2023-) at the Erasmus Mundus Master in Language and Communication Technologies (LCT) with two colleagues
• Programming and Language Technology for Students of Humanities (2024/2025) at bachelor level (University of Copenhagen), with a colleague

I previously taught other courses:

• Scientific Programming (2017-2022) at the M.S. in IT & Cognition (University of Copenhagen)

Teaching philosophy

We teach in a very heterogeneous group of students. My goal is that all students enjoy learning programming in all classes. Obviously, this is not a trivial task. I am still experimenting with different methodologies to please everybody, and mainly, to transmit knowledge.

The methods that I use include Jupyter notebooks, in which students have to solve practical problems. Every year we strive to increase the number of practical exercises, together with the theoretical sessions, as a practical session should always go with theoretical background. I always try to give simple examples to explain the intuition of models.

Teaching is a lifelong learning project, and thus, you never stop learning. That is why I really appreciate student evaluations, but also discussions with students, so that to see where I can improve myself.

Finally, I would like to state why is teaching so important for me. I love the feeling that somebody has learned something with me. Furthermore, if somebody has learned something and they have enjoyed during learning, I am even happier.

Every year, we use DataCamp as support material for students in the Scientific Programming course. DataCamp is a very intuitive learning platform for data science and analytics. DataCamp’s learn-by-doing methodology combines short expert videos and hands-on-the-keyboard exercises to help learners retain knowledge. DataCamp offers 325+ courses by expert instructors on topics such as importing data, data visualization, and machine learning. They’re constantly expanding their curriculum to keep up with the latest technology trends and to provide the best learning experience for all skill levels.