In late 2025, students and employees at GFI had the opportunity to join an evening course, spread over four sessions across five weeks, aimed at giving participants hands-on experience with building and tuning ML models.

Organised by Kjersti Birkeland Daae and Nilgun Kulan, and held by Robin Guillaume-Castel and Sigrid Passano Hellan, the course went through the basics of what an ML model really is and how a subset of models from the python packages SciKitLearn and PyTorch work. During the course, the participants solved exercises related to data pre-processing, hyperparameter selection and tuning.

For the last two sessions, the participants chose one of three half finished Neural Networks that consisted of different real world problems, with the goal of tuning them themselves. These were presented to the rest of the class at the end, with feedback and learning shared across the groups and projects.