Artificial Intelligence II 2018 (Audio) Prof. Dr. Michael Kohlhase
-
- Education
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.
Top Podcasts In Education
More by Friedrich-Alexander-Universität Erlangen-Nürnberg
ASC - Advanced Signal Processing and Communications Engineering (QHD 1920)
Friedrich-Alexander-Universität Erlangen-Nürnberg
Modern Optics 3: Quantum Optics 2019/2020 (QHD 1920)
Prof. Dr. Maria Chekhova
Foundations of Quantum Mechanics 2013 (SD 640)
Prof. Dr. Florian Marquardt
Lectures on Quantum Theory (Elite Graduate Programme) 2015 -Measurements (HD 1280)
Dr. Frederic P. Schuller
Quantum Computing 2019/2020 (QHD 1920)
Prof. Dr. Michael J. Hartmann
Deep Learning - Plain Version 2020 (QHD 1920)
Prof. Dr. Andreas Maier