066 645 Master programme Data Science

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

2023W-2024S (2018U)

TitlePrecon.HoursECTS
Master programme Data Science https://informatics.tuwien.ac.at/master/data-science/
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 2023W
Data-oriented Programming Paradigms
2.03.0
VU Experiment Design for Data Science
2.03.0
188.992 VU 2023W
Experiment Design for Data Science
2.03.0
VU Statistical Computing
2.03.0
105.731 VU 2024S
AKSTA 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 2023W
Advanced Methods for Regression and Classification
3.04.5
VU Machine Learning
3.04.5
184.702 VU 2024S
Machine Learning
3.04.5
184.702 VU 2023W
Machine Learning
3.04.5
Modul BDHPC/FD - Big Data and High Performance Computing - Foundations
9.0
VU Advanced Database Systems
4.06.0
VU Data-intensive Computing
2.03.0
Modul VAST/FD - Visual Analytics and Semantic Technologies - Foundations
9.0
VO Cognitive Foundations of Visualization
3.0
VO Information Visualization
2.03.0
188.305 VO 2023W
Information Visualization
2.03.0
VU Semantic Systems
2.03.0
188.399 VU 2023W
Introduction to Semantic Systems
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 2023W
Interdisciplinary Lecture Series on Data Science
1.01.0
PR Interdisciplinary Project in Data Science
4.05.0
194.047 PR 2023W
Interdisciplinary Project in Data Science canceled
4.05.0
194.147 PR 2023W
Interdisciplinary Project in Data Science
4.05.0
VU Domain-Specific Lectures in Data Science
3.0
194.068 VU 2023W
Domain-Specific Lectures in Data Science
2.03.0
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 2024S
Data Acquisition and Survey Methods
2.03.0
VO Data Stewardship
2.03.0
Modul FDS/EX - Fundamentals of Data Science - Extension
es dürfen maximal 18 ECTS absolviert werden
VU Advanced Cryptography
4.06.0
VU Communicating Data
2.03.0
VU Data Center Operations
2.03.0
UE Data Stewardship
2.03.0
VU Computational Social Science
2.03.0
VU Digital Humanism
2.03.0
194.072 VU 2023W
Digital Humanism
2.03.0
VU Internet Security
2.03.0
VU Organizational Aspects of IT-Security
2.03.0
VU Software Security
2.03.0
VU Sustainability in Computer Science
2.03.0
194.155 VU 2023W
Sustainability in Computer Science
2.03.0
VU Systems and Applications Security
4.06.0
VU User Research Methods
2.03.0
193.055 VU 2023W
User Research Methods
2.03.0
PR User Research Methods
2.03.0
193.056 PR 2023W
User Research Methods Project
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
VU Statistical Simulation and Computer Intensive Methods
2.03.0
107.330 VU 2023W
Statistical Simulation and Computerintensive Methods
2.03.0
Modul MLS/EX - Machine Learning and Statistics - Extension
es dürfen maximal 18 ECTS absolviert werden
VU Advanced Learning Methods
2.03.0
VU Advanced Modeling and Simulation
2.03.0
VU Advanced Reinforcement Learning
3.0
101.879 VU 2023W
AKNUM Advanced Reinfordement Learning
2.03.0
VU AI/ML in the Era of Climate Change
3.04.0
194.125 VU 2023W
AI/ML in the Era of Climate Change
3.04.0
VU AKNUM Reinforcement Learning
4.06.0
VU Algorithmic Social Choice
4.06.0
VU Applied Deep Learning
2.03.0
194.077 VU 2023W
Applied Deep Learning
2.03.0
VO Bayesian Statistics
2.03.0
UE Bayesian Statistics
1.02.0
VU Bayesian Statistics
3.05.0
105.173 VU 2023W
Bayesian Statistics
3.05.0
VU Business Intelligence
4.06.0
188.429 VU 2023W
Business Intelligence
4.06.0
VU Crypto Asset Analytics
2.03.0
VU Deep Learning for Visual Computing
2.03.0
VU General Regression Models
3.05.0
105.725 VU 2024S
General Regression Models
3.05.0
VO General Regression Models
2.03.0
UE General Regression Models
1.02.0
VU Generative AI
2.03.0
194.154 VU 2023W
Generative AI
2.03.0
VU Intelligent Audio and Music Analysis
3.04.5
194.039 VU 2023W
Intelligent Audio and Music Analysis
3.04.5
VO Introduction to Statistical Inference
3.04.5
UE Introduction to Statistical Inference
1.02.0
VU Machine Learning for Visual Computing
3.04.5
183.605 VU 2023W
Machine Learning for Visual Computing
3.04.5
VU Mathematical Programming
2.03.0
VU Modeling and Simulation
2.03.0
194.076 VU 2023W
Modeling and Simulation
2.03.0
VU Modelling and Simulation in Health Technology Assessment
2.03.0
194.094 VU 2023W
Modelling and Simulation in Health Technology Assessment
2.03.0
VO Multivariate Statistics
3.04.5
107.388 VO 2023W
Multivariate Statistics
3.04.5
UE Multivariate Statistics
1.01.5
107.391 UE 2023W
Multivariate Statistics
1.01.5
VU Probabilistic Programming and AI
4.06.0
194.150 VU 2023W
Probabilistic Programming and AI
4.06.0
VU Problem Solving and Search in Artificial Intelligence
2.03.0
181.190 VU 2024S
Problem Solving and Search in Artificial Intelligence
2.03.0
VU Security, Privacy and Explainability in Machine Learning
2.03.0
VU Self-Organizing Systems
3.04.5
188.413 VU 2023W
Self-Organizing Systems
3.04.5
VU Similarity Modeling 1
2.03.0
188.501 VU 2023W
Similarity Modeling 1 - Computational Seeing and Hearing
2.03.0
VU Similarity Modeling 2
2.03.0
188.498 VU 2023W
Similarity Modeling 2 - Computational Seeing and Hearing
2.03.0
VU Social Network Analysis
2.03.0
194.050 VU 2023W
Social Network Analysis
2.03.0
VU Theoretical Foundations and Research Topics in Machine Learning
2.03.0
194.100 VU 2023W
Theoretical Foundations and Research Topics in Machine Learning
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
VU Efficient Programs
2.03.0
185.190 VU 2023W
Efficient Programs
2.03.0
Modul BDHPC/EX - Big Data and High Performance Computing - Extension
es dürfen maximal 18 ECTS absolviert werden
VU Algorithmic Geometry
3.04.5
192.133 VU 2023W
Algorithmic Geometry
3.04.5
VU Algorithmics
4.06.0
186.814 VU 2023W
Algorithmics
4.06.0
VO Analysis 2
3.03.0
104.267 VO 2024S
Analysis 2
3.03.0
UE Analysis 2
2.04.5
104.268 UE 2024S
Analysis 2
2.04.5
VU Approximation Algorithms
2.03.0
186.102 VU 2023W
Approximation Algorithms
2.03.0
VU Complexity Analysis
2.03.0
VU Database Theory
2.03.0
181.140 VU 2023W
Database Theory
2.03.0
VU Fixed-Parameter Algorithms and Complexity
3.04.5
192.135 VU 2023W
Fixed-Parameter Algorithms and Complexity
3.04.5
VU Frontiers of Algorithms and Complexity
2.03.0
VU GPU Architectures and Computing
4.06.0
VU Graph Drawing Algorithms
3.04.5
VU Hands-On Cloud Native
4.06.0
194.131 VU 2024S
Hands-On Cloud Native
4.06.0
VU Heuristic Optimization Techniques
3.04.5
192.137 VU 2023W
Heuristic Optimization Techniques
3.04.5
VU High Performance Computing
3.04.5
184.725 VU 2023W
High Performance Computing
3.04.5
VO Nonlinear Optimization
2.03.0
105.147 VO 2023W
Nonlinear Programming
2.03.0
UE Nonlinear Optimization
1.02.0
105.652 UE 2023W
Nonlinear Programming
1.02.0
VU Optimization in Transport and Logistics
2.03.0
VU Structural Decompositions and Algorithms
2.03.0
VU Advanced Multiprocessor Programming
3.04.5
VU Randomized Algorithms
2.03.0
192.020 VU 2023W
Randomized Algorithms
2.03.0
Prüfungsfach Visual Analytics and Semantic Technologies - Core and Extension
Modul VAST/CO - Visual Analytics and Semantic Technologies - Core
6.0
VU Advanced Information Retrieval
2.03.0
UE Design and Evaluation of Visualisations
3.0
Modul VAST/EX - Visual Analytics and Semantic Technologies - Extension
es dürfen maximal 18 ECTS absolviert werden
VO Deductive Databases
2.03.0
192.067 VO 2023W
Deductive Databases
2.03.0
VU Description Logics and Ontologies
2.03.0
184.772 VU 2023W
Description Logics and Ontologies
2.03.0
VU Document Analysis
2.03.0
UE Information Visualization
1.01.5
188.308 UE 2023W
Information Visualization
1.01.5
VU KBS for Business Informatics
4.06.0
VU Knowledge-based Systems
4.06.0
VU Knowledge Graphs
2.03.0
VO Medical Image Processing
2.03.0
UE Medical Image Processing
2.03.0
VU Natural Language Processing and Information Extraction
2.03.0
194.093 VU 2023W
Natural Language Processing and Information Extraction
2.03.0
VO Processing of Declarative Knowledge
2.03.0
184.205 VO 2023W
Processing of Declarative Knowledge
2.03.0
VU Real-time Visualization
2.03.0
186.191 VU 2023W
Realtime Visualization
2.03.0
VU Semantic Technologies
2.03.0
VU Semi-Automatic Information and Knowledge Systems
2.03.0
VU Visual Data Science
2.03.0
186.868 VU 2023W
Visual Data Science
2.03.0
VU Visualization 2
3.04.5
186.833 VU 2023W
Visualization 2
3.04.5
Prüfungsfach Freie Wahlfächer und Transferable Skills
9.0
Catalog Elective Courses - Economics and Computer Science
Transferable Skills Catalogue
English TSK
VU Technical English Presentation A
3.0
015.111 VU 2024S
Technical English Presentation A
2.03.0
015.111 VU 2023W
Technical English Presentation A
2.03.0
VU Technical English Communication A
3.0
015.112 VU 2024S
Technical English Communication A
2.03.0
015.112 VU 2023W
Technical English Communication A
2.03.0
VU Technical English Presentation B
3.0
015.113 VU 2024S
Technical English Presentation B
2.03.0
015.113 VU 2023W
Technical English Presentation B
2.03.0
VU Technical English Communication B
3.0
015.115 VU 2024S
Technical English Communication B
2.03.0
015.115 VU 2023W
Technical English Communication B
2.03.0
VO European Union - Institutions, Policies and Future Challenges
2.0
164.287 VO 2023W
European Union - Institutions, Policies and Future Challenges
1.52.0
VU Global Strategy, Markets and Politics
2.03.0
SE Science and the quest for knowledge
1.01.0
259.446 SE 2023W
Science and the quest for knowledge
1.01.0
VO Creativity Engineering
3.0
015.100 VO 2023W
Creativity Engineering
2.03.0
VU Searching prior art based on patent applications
2.03.0
061.001 VU 2024S
Searching prior art based on patent applications
2.03.0
VU Collaboration and Co-Creation
2.03.0
061.006 VU 2024S
Collaboration and Co-Creation
2.03.0
VU E&I Garage - Business Model Development
3.05.0
330.255 VU 2024S
E&I Garage - Business Model Development
3.05.0
Modul Freie Wahlfächer und Transferable Skills
SE Coaching als Führungsinstrument 2
2.03.0
SE Critical Algorithm Studies
2.03.0
SE Didaktik in der Informatik
2.03.0
194.042 SE 2023W
Informatics didactics
2.03.0
VO EDV-Vertragsrecht
1.01.5
280.239 VO 2023W
Law of IT-Contracts
1.01.5
VO Einführung in die Wissenschaftstheorie I
2.03.0
VO Einführung in Technik und Gesellschaft
2.03.0
SE Folgenabschätzung von Informationstechnologien
2.03.0
VU Forschungsmethoden
2.03.0
185.A34 VU 2023W
Research Methods
2.03.0
VO Frauen in Naturwissenschaft und Technik
2.03.0
VU Kommunikation und Moderation
2.03.0
SE Kommunikationstechnik
1.01.5
184.004 SE 2023W
Communication techniques
1.01.5
VU Kooperatives Arbeiten
2.03.0
VU Präsentation und Moderation
2.03.0
185.A62 VU 2023W
Presentation and Moderation
2.03.0
SE Privatissimum aus Fachdidaktik Informatik
4.04.0
SE Scientific Presentation and Communication
2.03.0
VU Softskills für TechnikerInnen
2.03.0
181.208 VU 2024S
Softskills for technicians
2.03.0
181.208 VU 2023W
Softskills for technicians
2.03.0
VU Techniksoziologie und Technikpsychologie
2.03.0
VO Theorie und Praxis der Gruppenarbeit
2.03.0
SE Wissenschaftliche Methodik
2.03.0
Diplomarbeit und kommissionelle Gesamtprüfung
30.0
SE Seminar für Diplomand_innen
1.01.5
180.772 SE 2023W
Seminar for Master Students in Data Science
1.01.5
Thesis Diploma thesis
27.0
Final exam Final board exam
1.5
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