066 645 Master programme Data Science

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

2024W-2025S (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
VU Experiment Design for Data Science
2.03.0
VU Statistical Computing
2.03.0
105.731 VU 2025S
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 2024W
Advanced Methods for Regression and Classification
3.04.5
VU 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
VU 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
PR Interdisciplinary Project in Data Science
4.05.0
VU Domain-Specific Lectures in Data Science
3.0
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 2025S
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
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
VU Systems and Applications Security
4.06.0
VU User Research Methods
2.03.0
PR 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
VU Statistical Simulation and Computer Intensive Methods
2.03.0
107.330 VU 2024W
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
VU 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
VO Bayesian Statistics
2.03.0
UE Bayesian Statistics
1.02.0
VU Bayesian Statistics
3.05.0
VU 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
VO General Regression Models
2.03.0
UE General Regression Models
1.02.0
VU Generative AI
2.03.0
VU 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
VU Mathematical Programming
2.03.0
VU Modeling and Simulation
2.03.0
VU Modelling and Simulation in Health Technology Assessment
2.03.0
VO Multivariate Statistics
3.04.5
107.388 VO 2024W
Multivariate Statistics
3.04.5
UE Multivariate Statistics
1.01.5
107.391 UE 2024W
Multivariate Statistics
1.01.5
VU Probabilistic Programming and AI
4.06.0
VU 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
VU Similarity Modeling 1
2.03.0
VU Similarity Modeling 2
2.03.0
VU Social Network Analysis
2.03.0
VU 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
Modul BDHPC/EX - Big Data and High Performance Computing - Extension
es dürfen maximal 18 ECTS absolviert werden
VU Algorithmic Geometry
3.04.5
VU Algorithmics
4.06.0
VO Analysis 2
3.03.0
UE Analysis 2
2.04.5
VU Approximation Algorithms
2.03.0
VU Complexity Analysis
2.03.0
VU Database Theory
2.03.0
VU 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
VU Heuristic Optimization Techniques
3.04.5
VU High Performance Computing
3.04.5
VO Nonlinear Optimization
2.03.0
105.147 VO 2024W
Nonlinear Programming
2.03.0
UE Nonlinear Optimization
1.02.0
105.652 UE 2024W
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
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
VU Description Logics and Ontologies
2.03.0
VU Document Analysis
2.03.0
UE 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
VO Processing of Declarative Knowledge
2.03.0
VU Research Topics in Natural Language Processing
2.03.0
VU Real-time 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
VU 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
VU Technical English Communication A
3.0
VU Technical English Presentation B
3.0
VU Technical English Communication B
3.0
VO European Union - Institutions, Policies and Future Challenges
2.0
164.287 VO 2024W
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
VO Creativity Engineering
3.0
VU Searching prior art based on patent applications
2.03.0
VU Collaboration and Co-Creation
2.03.0
VU E&I Garage - Business Model Development
3.05.0
Modul Freie Wahlfächer und Transferable Skills
SE Coaching als Führungsinstrument 1
2.03.0
SE Coaching als Führungsinstrument 2
2.03.0
SE Didaktik in der Informatik
2.03.0
VO EDV-Vertragsrecht
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
VO Frauen in Naturwissenschaft und Technik
2.03.0
SE Gruppendynamik
3.03.0
PR IT-Projekte für Jugendliche
3.0
UE IT Projekte für Jugendliche
1.5
VU Kommunikation und Moderation
2.03.0
SE Kommunikation und Rhetorik
2.03.0
SE Kommunikation und Rhetorik 2
2.03.0
SE Kommunikationstechnik
1.01.5
VU Kooperatives Arbeiten
2.03.0
VU Präsentation und Moderation
2.03.0
VO Präsentation, Moderation und Mediation
1.01.5
UE Präsentation, Moderation und Mediation
2.02.0
VU Präsentations- und Verhandlungstechnik
2.03.0
SE Privatissimum aus Fachdidaktik Informatik
4.04.0
VU Rhetorik, Körpersprache, Argumentationstraining
2.03.0
SE Scientific Presentation and Communication
2.03.0
VU Softskills für TechnikerInnen
2.03.0
VU Techniksoziologie und Technikpsychologie
2.03.0
VO Theorie und Praxis der Gruppenarbeit
2.03.0
SE VWA Mentoring I
2.02.0
SE VWA Mentoring II
2.02.0
VO Zwischen Karriere und Barriere
2.03.0
Diplomarbeit und kommissionelle Gesamtprüfung
30.0
SE Seminar für Diplomand_innen
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.

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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