We teach several courses in the field of artificial intelligence.
The course provides students with a theoretical understanding and practical experience in the core areas of artificial intelligence such as state space search algorithms, constraint satisfaction problems, machine learning, knowledge representation with propositional logic, probabilistic reasoning and automated planning.
Course website: TDDC17
This course covers automated planning, a central topic in AI, with hands-on experience in creating planning models to solve sequential decision making problems, exploring its numerous applications from logistics to space exploration.
Course website: TDDD48
Foundations of AI and Machine Learning
This course gives a very broad introduction into Artificial Intelligence and Machine learning for students without computer-science background. The goal is to give the students the means to communicate with AI/ML experts when it comes to using techniques from these fields in projects in their own field of expertise, such as mechanical engineering, product design, or environmental management.
Course website: TDDE56
Graph Learning (PhD course)
In this seminar, we cover different neural-network architectures for representing graphs. The participants read and present selected papers, which will be discussed during the meetings.
Course website: Graph Learning