Studienhandbuch der JKU Linz
Seitenbereiche:
Sprachauswahl:
Sprache:
[
DE
]
.
EN
Studienhandbuch-Login
Benutzername
Passwort
.
Menü
Übersicht
Alle Curricula
Externe Tools
KUSSS
Auwea NG
Positionsanzeige
Artificial Intelligence
»
(*)
Area of Specialization
Inhalt
[
993SCDS19
] Studienfach
(*)
Computer and Data Science
Versionsauswahl
Version
2019W
(*)
Leider ist diese Information in Deutsch nicht verfügbar.
Workload
Form der Prüfung
Ausbildungslevel
Studienfachbereich
VerantwortlicheR
Anbietende Uni
Gliederung
M1 - Master 1. Jahr
Informatik
Sepp Hochreiter
Johannes Kepler Universität Linz
Detailinformationen
Quellcurriculum
Masterstudium Artificial Intelligence 2019W
Ziele
(*)
Specialization topics in computer and data science.
Lehrinhalte
(*)
The contents of this subject result from the contents of its courses.
Untergeordnete Studienfächer, Module und Lehrveranstaltungen
KV
(*)
Basic Methods of Data Analysis
UE
(*)
Computational Logics for AI
VL
(*)
Computational Logics for AI
UE
(*)
Introduction to Computational Statistics
VL
(*)
Introduction to Computational Statistics
UE
(*)
Machine Learning: Supervised Techniques
VL
(*)
Machine Learning: Supervised Techniques
UE
(*)
Machine Learning: Unsupervised Techniques
VL
(*)
Machine Learning: Unsupervised Techniques
UE
(*)
Programming in Python II
VL
(*)
Programming in Python II
UE
(*)
Reinforcement Learning
VL
(*)
Reinforcement Learning
UE
(*)
Statistics for AI
VL
(*)
Statistics for AI
UE
(*)
Visual Analytics
UE
(*)
Knowledge Representation and Learning
VL
(*)
Knowledge Representation and Learning
UE
(*)
Planning and Reasoning in Artificial Intelligence
VL
(*)
Planning and Reasoning in Artificial Intelligence
UE Softwareentwicklung 2
VL Softwareentwicklung 2
KV
(*)
Big Data Management and Processing
KV
(*)
Computational Data Analytics
KV
(*)
Conceptual Data Modeling
KV
(*)
Debugging
KV
(*)
Emerging Computer Technologies
KV
(*)
Hardware Design
VL
(*)
Information Displays
KV
(*)
Information Visualization
KV
(*)
Knowledge Based Systems
UE
(*)
Learning from User-generated Data
VL
(*)
Learning from User-generated Data
UE
(*)
Machine Learning and Pattern Classification
VL
(*)
Machine Learning and Pattern Classification
KV
(*)
Mobile Computing
UE
(*)
Model Checking
VL
(*)
Model Checking
KV
(*)
Multimedia Search and Retrieval
KV
(*)
Parallel Computing
KV
(*)
Principles of Cooperation
KV
(*)
Principles of Interaction
KV
(*)
SAT Solving
KV
(*)
Semantic Data Modeling and Applications
VL
(*)
Visual Analytics
IK Operations Research
KS Operations Research
KV
(*)
Statistical Principles of Data Science
SE Computational Logistics: Metaheuristiken
SE Computational Logistics: Optimierung