Artificial Intelligence II 2018 (QHD 1920 - Video & Folien)
Prof. Dr. Michael Kohlhase
This course covers the foundations of Artificial Intelligence (AI), in particular reasoning under uncertainty, machine learning and (if there is time) natural language understanding. This course builds on the course Artificial Intelligence I from the preceding winter semester and continues it
Learning Goals and Competencies Technical, Learning, and Method Competencies
Knowledge: The students learn foundational representations and algorithms in AI. Application: The concepts learned are applied to examples from the real world (homeworks ). Analysis: By modeling human cognitive abilities, students learn to assess and understand human intelligence better.
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