(*) Leider ist diese Information in Deutsch nicht verfügbar.
Workload
Form der Prüfung
Ausbildungslevel
Studienfachbereich
VerantwortlicheR
Anbietende Uni
21 ECTS
Kumulative Fachprüfung
M1 - Master 1. Jahr
Informatik
Sepp Hochreiter
Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum
Masterstudium Artificial Intelligence 2022W
Ziele
(*)Classical methods in AI rely on symbolic reasoning based on logic and mathematics. On the one hand, a focus of this elective track is on deductive reasoning, including model checking and theorem proving, techniques which are also essential for software and hardware verification. On the other hand, students can focus on specialized mathematical topics in the fields of analysis, numerics, and statistics, which underpin modern AI technologies.
Lehrinhalte
(*)The contents of this subject result from the contents of its courses.
Sonstige Informationen
(*)Rules for the elective track "Symbolic AI and Mathematical Foundations": (a) Students need to complete 21 ECTS points in total from both sub-categories ("Symbolic AI" and "Mathematical Foundations"). (b) Students need to choose a “focus” sub-category from which at least 13.5 ECTS points have to be completed. If the focus is the sub-category “Symbolic AI”, the following courses must be completed:
993TASMKPLV22: VL Knowledge Representation and Learning (3 ECTS)
993TASMKPLU22: UE Knowledge Representation and Learning (1.5 ECTS)
993TASMPRAV22: VL Planning and Reasoning in Artificial Intelligence (3 ECTS)
993TASMPRAU22: UE Planning and Reasoning in Artificial Intelligence (1.5 ECTS).
Untergeordnete Studienfächer, Module und Lehrveranstaltungen
