066 645 Master programme Data Science

  • Show all courses of the academic year of which the selected semester is part of.

2018W-2019S (2018U)

TitlePrecon.HoursECTS
Master programme Data Science http://www.informatik.tuwien.ac.at/studium/angebot/master/DataScience
120.0
Prüfungsfach Data Science - Foundations
36.0
Modul FDS/FD - Fundamentals of Data Science - Foundations
9.0
VU Data-oriented Programming Paradigms
2.03.0
188.995 VU 2018W
Data-oriented Programming Paradigms
2.03.0
VU Experiment Design for Data Science
2.03.0
188.992 VU 2018W
Experiment Design for Data Science
2.03.0
VO Statistical Computing
2.03.0
107.106 VO 2019S
Statistical Computing
2.03.0
Modul MLS/FD - Machine Learning and Statistics - Foundations
9.0
VU Advanced Methods for Regression and Classification
3.04.5
105.707 VU 2018W
Advanced Methods for Regression and Classification
3.04.5
VU Machine Learning
3.04.5
184.702 VU 2019S
Machine Learning
3.04.5
184.702 VU 2018W
Machine Learning
3.04.5
Modul BDHPC/FD - Big Data and High Performance Computing - Foundations
9.0
VU Data-intensive Computing
2.03.0
194.048 VU 2019S
Data-intensive Computing
2.03.0
VU Datenbanksysteme Vertiefung
4.06.0
184.780 VU 2019S
Advanced Database Systems
4.06.0
Modul VAST/FD - Visual Analytics and Semantic Technologies - Foundations
9.0
VO Cognitive Foundations of Visualization
2.03.0
187.A44 VO 2019S
Cognitive foundations of visualisation
2.03.0
VU Einführung in Semantic Systems
2.03.0
188.399 VU 2018W
Introduction to Semantic Systems
2.03.0
VO Information Visualization
2.03.0
186.141 VO 2019S
Information Visualization
2.03.0
188.305 VO 2018W
Information Visualization
2.03.0
Prüfungsfach Domain-Specific Aspects of Data Science
9.0
Modul DSA - Domain-Specific Aspects of Data Science
9.0
VU Interdisciplinary Lecture Series on Data Science
1.01.0
194.046 VU 2018W
Interdisciplinary Lecture Series on Data Science
1.01.0
PR Interdisciplinary Project in Data Science
4.05.0
194.047 PR 2018W
Interdisciplinary Project in Data Science
4.05.0
194.060 PR 2019S
Interdisciplinary Project in Data Science
4.05.0
Prüfungsfach Fundamentals of Data Science - Core and Extension
Modul FDS/CO - Fundamentals of Data Science - Core
6.0
VU Data Acquisition and Survey Methods
2.03.0
105.708 VU 2019S
Data Acquisition and Survey Methods
2.03.0
VO Data Stewardship
2.03.0
194.044 VO 2019S
Data Stewardship
2.03.0
Modul FDS/EX - Fundamentals of Data Science - Extension
VU Communicating Data
2.03.0
VU Data Center Operations
2.03.0
UE Data Stewardship
2.03.0
194.045 UE 2019S
Data Stewardship
2.03.0
VU Internet Security
2.03.0
188.366 VU 2019S
Internet Security
2.03.0
VU Organizational Aspects of IT-Security
2.03.0
188.312 VU 2018W
Organizational Aspects of IT-Security
2.03.0
PR User Research Methoden
2.03.0
187.A69 PR 2018W
User Research Methods Project
2.03.0
VU Software Security
2.03.0
188.959 VU 2019S
Software Security
2.03.0
VU User Research Methoden
2.03.0
187.A68 VU 2018W
User Research Methods
2.03.0
Prüfungsfach Machine Learning and Statistics - Core and Extension
Modul MLS/CO - Machine Learning and Statistics - Core
6.0
VU Recommender Systems
2.03.0
194.035 VU 2019S
Recommender Systems
2.03.0
VU Statistical Simulation and Computer Intensive Methods
2.03.0
107.330 VU 2018W
Statistical Simulation and Computerintensive Methods
2.03.0
Modul MLS/EX - Machine Learning and Statistics - Extension
VU Advanced Learning Methods
2.03.0
VU Advanced Modeling and Simulation
2.03.0
VO Bayesian Statistics
2.03.0
107.395 VO 2019S
Bayesian Statistics
2.03.0
UE Bayesian Statistics
1.02.0
107.397 UE 2019S
Bayesian Statistics
1.02.0
VU Business Intelligence
4.06.0
188.429 VU 2018W
Business Intelligence
4.06.0
VU Intelligent Audio and Music Analysis
3.04.5
194.039 VU 2018W
Intelligent Audio and Music Analysis
3.04.5
VU Deep Learning for Visual Computing
2.03.0
183.663 VU 2018W
Deep Learning for Visual Computing
2.03.0
VO Multivariate Statistics
3.04.5
107.388 VO 2018W
Multivariate Statistics
3.04.5
VO General Regression Models
2.03.0
107.347 VO 2019S
General Regression Models
2.03.0
UE General Regression Models
1.02.0
107.348 UE 2019S
General Regression Models
1.02.0
VU Similarity Modeling 2
2.03.0
188.498 VU 2018W
Similarity Modeling 2
2.03.0
VO Introduction to Statistical Inference
3.04.5
UE Introduction to Statistical Inference
1.02.0
VU Mathematical Programming
2.03.0
186.835 VU 2019S
Mathematical Programming
2.03.0
VU Modeling and Simulation
2.03.0
101.732 VU 2018W
Modeling and Simulation
2.03.0
VU Security, Privacy and Explainability in Machine Learning
2.03.0
194.055 VU 2019S
Security, Privacy and Explainability in Machine Learning
2.03.0
UE Multivariate Statistics
1.01.5
107.391 UE 2018W
Multivariate Statistics
1.01.5
VU Problem Solving and Search in Artificial Intelligence
2.03.0
181.190 VU 2019S
Problem Solving and Search in Artificial Intelligence
2.03.0
VU Self-Organizing Systems
3.04.5
188.413 VU 2018W
Self-Organizing Systems
3.04.5
VU Social Network Analysis
2.03.0
194.050 VU 2018W
Social Network Analysis
2.03.0
Prüfungsfach Big Data and High-Performance Computing - Core and Extension
Modul BDHPC/CO - Big Data and High Performance Computing - Core
6.0
VU Basics of Parallel Computing
2.03.0
191.114 VU 2019S
Basics of Parallel Computing
2.03.0
VU Energy-efficient Distributed Systems
2.03.0
194.049 VU 2019S
Energy-efficient Distributed Systems
2.03.0
Modul BDHPC/EX - Big Data and High Performance Computing - Extension
VU Algorithmics
4.06.0
186.814 VU 2018W
Algorithmics
4.06.0
VO Analysis 2
3.03.0
104.267 VO 2019S
Analysis 2
3.03.0
UE Analysis 2
2.04.5
104.268 UE 2019S
Analysis 2
2.04.5
VU Algorithmic Geometry
2.03.0
186.122 VU 2018W
Algorithmic Geometry
2.03.0
VU Approximation Algorithms
2.03.0
186.102 VU 2018W
Approximation Algorithms
2.03.0
VU Complexity Analysis
2.03.0
VU Effiziente Programme
2.03.0
185.190 VU 2018W
Efficient Programs
2.03.0
VU Database Theory
2.03.0
181.140 VU 2019S
Database Theory canceled
2.03.0
VU Fixe-Parameter Algorithms and Complexity
2.03.0
186.855 VU 2018W
Fixed-Parameter Algorithms and Complexity
2.03.0
VU GPU Architectures and Computing
4.06.0
182.731 VU 2019S
GPU Architectures and Computing
4.06.0
VU Graph Drawing Algorithms
2.03.0
192.053 VU 2019S
Graph Drawing Algorithms
2.03.0
VU High Performance Computing
3.04.5
184.725 VU 2018W
High Performance Computing
3.04.5
VU Heuristic Optimization Techniques
2.03.0
186.112 VU 2018W
Heuristic Optimization Techniques
2.03.0
VU Optimization in Transport and Logistics
2.03.0
VO Nichtlineare Optimierung
2.03.0
105.147 VO 2018W
Nonlinear Programming
2.03.0
VU Structural Decompositions and Algorithms
2.03.0
186.856 VU 2019S
Structural Decompositions and Algorithms
2.03.0
UE Nichtlineare Optimierung
1.02.0
105.652 UE 2018W
Nonlinear Programming
1.02.0
VU Weiterführende Multiprocessor Programmierung
3.04.0
Prüfungsfach Visual Analytics and Semantic Technologies - Core and Extension
Modul VAST/CO - Visual Analytics and Semantic Technologies - Core
6.0
UE Design and Evaluation of Visualisations
2.03.0
187.A46 UE 2019S
Design and Evaluation of visualisations
2.03.0
VU Advanced Information Retrieval
2.03.0
188.980 VU 2019S
Advanced Information Retrieval
2.03.0
Modul VAST/EX - Visual Analytics and Semantic Technologies - Extension
VO Deductive Databases
2.03.0
192.067 VO 2018W
Deductive Databases
2.03.0
VU Description Logics and Ontologies
2.03.0
184.772 VU 2018W
Description Logics and Ontologies canceled
2.03.0
VU Informationsdesign und Visualisierung
2.03.0
VU Information Extraction
2.03.0
UE Information Visualization
1.01.5
186.143 UE 2019S
Information Visualization
1.01.5
188.308 UE 2018W
Information Visualization
1.01.5
VU KBS for Business Informatics
4.06.0
VU Knowledge-based Systems
4.06.0
184.730 VU 2019S
Knowledge-based Systems
4.06.0
VO Processing of Declarative Knowledge
2.03.0
184.205 VO 2018W
Processing of Declarative Knowledge
2.03.0
VU Real-time Visualization
2.03.0
186.191 VU 2018W
Realtime Visualization
2.03.0
VU Semantic Web Technologies
2.03.0
184.729 VU 2018W
Semantic Web Technologies canceled
2.03.0
VU Semi-Automatic Information and Knowledge Systems
2.03.0
188.387 VU 2019S
Semi-Automatic Information and Knowledge Systems
2.03.0
VU Visual Data Science
2.03.0
186.868 VU 2018W
Visual Data Science
2.03.0
VU Visualization 2
3.04.5
186.833 VU 2019S
Visualization 2
3.04.5
Prüfuchsfach Freie Wahlfächer und Transferable Skills
9.0
Diplomarbeit und kommissionelle Gesamtprüfung
30.0
Final exam Final board exam
3.0
Thesis Diploma thesis
27.0
SE Seminar für Diplomand_innen
1.01.5
180.772 SE 2019S
Seminar for Master Students in Data Science
1.01.5
180.772 SE 2018W
Seminar for Master Students in Data Science
1.01.5
Responsible dean of academic affairs
For questions regarding the curriculum please contact the responsible dean of academic affairs.

Legend

Courses belong to the introductory and orientation phase ("Studieneingangs- und Orientierungsphase")
Courses belong to the introductory interview ("Studieneingangsgespräch")
Courses require the completion of the introductory and orientation phase
Courses require the completion of the introductory interview STEG