An important trend today is systems and functionality that can learn, improve and adapt to changing environments. In this course you will study important techniques that enable computer programs to improve automatically through experience. The course covers decision trees, artificial neural nets, evolutionary computation, fuzzy systems, probabilistic learning, and reinforcement learning. The course is well connected to Robotics, Computer Science, and Intelligent Embedded Systems programs.
Occasions for this course
Autumn semester 2021
2021-11-08 - 2022-01-16 (part time 50%)
Course syllabus & literatureSee course plan and literature list (DVA427)
90 credits including Programming 7.5 credits and Data Structures, Algorithms and Program Development 7.5 credits, or equivalent. In addition Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English exemption is made from the requirement in Swedish course B/Swedish course 3.