120 credits including 90 credits in computer science, technology, mathematics, chemistry, physics, or materials science. Proficiency in English equivalent to the Swedish upper secondary course English 6.
Introduction to recent digitalisation concepts of technological importance: Internet of Things, wireless communication systems, and its interrelation with energy storage. Introduction to machine learning and artificial intelligence: its terminology, an overview of basic algorithms and literature study on its use in modelling energy storage. Use of established tools and algorithms for machine learning in modelling energy storage. To pass, you must be able to: discuss the energy profile for Internet of Things applications, wireless systems, and other emerging technologies explain and motivate use cases in which artificial intelligence tools can be used in the field of chemical energy storage explain and compare basic machine learning methods in the context of modelling energy storage use machine learning techniques and software to model energy storage.
