Machine LearningSemester Course

Computer Science
Week-Long Study Tour
London or Berlin
Major Discipline(s)
Computer Science, Information Science, Mathematics
Core Course
Fall/Spring semester

Spotify, the Swedish giant, relies on machine learning to personalize the music experience of millions of users. Scania, the Swedish, world-leading provider of transport solutions, is using machine learning to develop self-driving trucks. Sweden is a renowned hub for technical startups developing the future of machine learning. Applications include robotics, computer vision, speech recognition and synthesis, traffic predictions, and medical diagnostics.

Machine learning utilizes training data to develop models capable of identifying patterns, classifying large amounts of information, making predictions or decisions, and providing insights embedded in vast and complex data. This course offers a hands-on approach to the theory and practice of machine learning, with real-world applications. It focuses on training datasets, machine learning approaches, and the fitting and optimization of models.


Niklas Furderer

DIS Stockholm Semester Faculty

M.Sc. (Data Science, KTH Royal Institute of Technology (Stockholm), 2018). M.Sc. (Data Science, Universidad Politécnica de Madrid (Madrid), 2017. B.Sc. (International Management for Business and Information Technology, Duale Hochschule Baden-Württemberg (Stuttgart), 2016). Machine Learning Engineer, Nectarine Health, 2018-2022. Data Scientist / Product Data Analyst, Grace Health, 2022-2023. Senior Data Science Consultant, Crowd Collective, 2023-present. With DIS since 2024.

Lucy McCarren

DIS Stockholm Semester Faculty

Ph.D. (Candidate at the Department of Technology and Health at KTH). Research focus on socio-technical studies of Artificial Intelligence, in particular applications of conversational AI for elderly care. Master of Science in Machine Learning, KTH (2023). Bachelor of Science in Mathematics, Dublin City University (2015).