About this course
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.
Syllabus
Pre-requisites
One year of computer science, a course in algorithms and data structures, one course in linear algebra at university level. A course in statistics is recommended. Knowledge of at least one programming language (e.g. Python/Javascript/Java/C++/Matlab).
Faculty
Aniss Aiman Medbouhi
FacultyPh.D. candidate in Computer Science, KTH Royal Institute of Technology (2022–present). M.Sc. double degree in Computer Science and Engineering/General Engineering, KTH Royal Institute of Technology/Ecole Centrale Marseille (2017–2021). Previous experience developing an algorithm of toxicity risk prediction for anti-cancer chemotherapy and supporting KTH’s Machine Learning and Artificial Intelligence courses. With DIS since 2025.
Lucy McCarren
FacultyPh.D. candidate, Department of Technology and Health, KTH Royal Institute of Technology (2023–present). M.S. in Machine Learning, KTH Royal Institute of Technology (2023). B.S. in Mathematics, Dublin City University (2015). Research focus on socio-technical studies of Artificial Intelligence, in particular applications of conversational AI for elderly care. Previous experience processing and visualizing large datasets as Data Analyst at Nordnet Bank AB and developing statistical pricing models as BI Consultant at FD Technologies. With DIS since 2024.