TU Wien: Masterstudium Data Science
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| Links | Ehemalige LVAs, Studienplan, TISS |
|---|---|
| VoWi-Stats |
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Obligation: Pflichtfach
BDHPC/FD - Big Data and High Performance Computing - Foundations
DSA - Domain-Specific Aspects of Data Science
- Interdisciplinary Lecture Series on Data Science VU (Hanbury)
- Interdisciplinary Lecture Series on Data Science VU (Rauber)
- Interdisciplinary Project in Data Science PR (Hanbury)
FDS/FD - Fundamentals of Data Science - Foundations
- AKSTA Statistical Computing VU (Vana Gür)
- Datenorientierte Programmierparadigmen VU (Hanbury)
- Experiment Design for Data Science VU (Rauber)
MLS/FD - Machine Learning and Statistics - Foundations
VAST/FD - Visual Analytics and Semantic Technologies - Foundations
- Cognitive Foundations of Visualization VO (Weiss)
- Einführung in Semantic Systems VU (Hose)
- Informationsvisualisierung VO (Aigner)
- Informationsvisualisierung VO (Matkovic)
Obligation: Gebundenes Wahlfach
BDHPC/CO - Big Data and High Performance Computing - Core
BDHPC/EX - Big Data and High Performance Computing - Extension
- Algorithmics VU (Szeider)
- Frontiers of Algorithms and Complexity VU (Hoang)
- Graph Drawing Algorithms VU (Nöllenburg)
- Hands-On Cloud Native VU (Rauber)
- Hybrid Quantum - Classical Systems VU (De Maio)
- Nichtlineare Optimierung UE (Tragler)
- Nichtlineare Optimierung VO (Tragler)
- Optimization in Transport and Logistics VU (Raidl)
- Randomized Algorithms VU (Sorge)
FDS/EX - Fundamentals of Data Science - Extension
- Digital Humanism VU (Knees)
- Sustainability in Computer Science VU (Kappel)
- Systems and Applications Security VU (Lindorfer)
MLS/EX - Machine Learning and Statistics - Extension
- AI ML in the Era of Climate Change VU (Brandic)
- AKNUM Advanced Reinforcement Learning VU (Heitzinger)
- AKNUM Reinforcement Learning VU (Heitzinger)
- Applied Deep Learning VU (Eidenberger)
- Applied Deep Learning VU (Lukasiewicz)
- Deep Learning for Visual Computing VU (Hermosilla Casajus)
- Generative AI VU (Heitzinger)
- Generative AI VU (Neidhardt)
- Intelligent Audio and Music Analysis VU (Knees)
- Modelling and Simulation in Health Technology Assessment VU (Popper)
- Modelling and Simulation in Health Technology Assessment VU (Urach)
- Selbstorganisierende Systeme VU (Rauber)
VAST/CO - Visual Analytics and Semantic Technologies - Core
VAST/EX - Visual Analytics and Semantic Technologies - Extension
- Document Analysis VU (Sablatnig)
- Knowledge Graphs VU (Sallinger)
- Medizinische Bildverarbeitung UE (Langs)
- Medizinische Bildverarbeitung VO (Sablatnig)
Obligation: Keine Angabe
BDHPC/CO - Big Data and High Performance Computing - Core
BDHPC/EX - Big Data and High Performance Computing - Extension
- Advanced Multiprocessor Programming VU (Träff)
- Algorithmic Geometry VU (Nöllenburg)
- Analysis 2 UE (Panholzer)
- Analysis 2 UE (diverse)
- Analysis 2 VO (Müllner)
- Approximation Algorithms VU (Kellerer)
- Complexity Analysis VU (Eiter)
- Datenbanktheorie VU (Lanzinger)
- Datenbanktheorie VU (Pichler)
- Fixed-Parameter Algorithms and Complexity VU (Ganian)
- GPU Architectures and Computing VU (Bartocci)
- Heuristic Optimization Techniques VU (Raidl)
- High Performance Computing Hochleistungsrechnen VU (Träff)
- Structural Decompositions and Algorithms VU (Peitl)
DSA - Domain-Specific Aspects of Data Science
English TSK
- Collaboration and Co-Creation VU (Jerlich)
- Creativity Engineering VO (Jerlich)
- E&I Garage - Business Model Development VU (Vasilescu)
- European Union - Institutions Policies and Future Challenges VO (Grasserbauer)
- Science and the quest for knowledge SE (Pont)
- Searching prior art based on patent applications VU (Hofmann)
- Technical English Communication VU (Crowder)
- Technical English Presentation VU (Crowder)
FDS/CO - Fundamentals of Data Science - Core
FDS/EX - Fundamentals of Data Science - Extension
- Data Stewardship UE (Rauber)
- User Research Methoden PR (Purgathofer)
- User Research Methoden PR (Wozniak)
- User Research Methoden VU (Purgathofer)
- User Research Methoden VU (Wozniak)
MLS/CO - Machine Learning and Statistics - Core
- Recommender Systems VU (Neidhardt)
- Statistische Simulation und computerintensive Methoden VU (Posekany)
MLS/EX - Machine Learning and Statistics - Extension
- Algorithmic Social Choice VU (Chen)
- Allgemeine Regressionsmodelle VU (Bura)
- Bayes-Statistik VU (Avalos Pacheco)
- Bayes-Statistik VU (Bura)
- Business Intelligence VU (Rauber)
- Crypto Asset Analytics VU (Maffei)
- Machine Learning for Visual Computing VU (Reiter)
- Mathematical Programming VU (Raidl)
- Modeling and Simulation VU (Bicher)
- Multivariate Statistik UE (Filzmoser)
- Multivariate Statistik VO (Filzmoser)
- Probabilistic Programming and AI VU (Böck)
- Probabilistic Programming and AI VU (Cito)
- Problem Solving and Search in Artificial Intelligence VU (Musliu)
- Sicherheit Privacy und Erklärbarkeit in Maschinellem Lernen VU (Rauber)
- Similarity Modeling 1 - Computational Seeing and Hearing VU (Eidenberger)
- Similarity Modeling 2 - Computational Seeing and Hearing VU (Eidenberger)
- Social Network Analysis VU (Neidhardt)
- Theoretical Foundations and Research Topics in Machine Learning VU (Gärtner)
VAST/CO - Visual Analytics and Semantic Technologies - Core
VAST/EX - Visual Analytics and Semantic Technologies - Extension
- Deductive Databases VO (Simkus)
- Description Logics and Ontologies VU (Ortiz de la Fuente)
- Echtzeit-Visualisierung VU (Waldner)
- Informationsvisualisierung UE (Miksch)
- Informationsvisualisierung UE (Waldner)
- Knowledge-based Systems VU (Egly)
- Natural Language Processing and Information Extraction VU (Hanbury)
- Research topics in natural language processing VU (Recski)
- Semantic Technologies VU (Ortiz de la Fuente)
- Semi-Automatic Information and Knowledge Systems VU (Sabou)
- Verarbeitung deklarativen Wissens VO (Eiter)
- Visual Data Science VU (Schmidt)
- Visualisierung 2 VU (Waldner)
_no module mapping_
- AKSTA Statistical Computing VO (Posekany)
- AKSTA Statistical Computing VU (Posekany)
- Advanced Aspects of Connected Car IT VU (Grechenig)
- Advanced Cryptography VU (Fuchsbauer)
- Analysis 2 UE (Müllner)
- Analysis 2 VO (Panholzer)
- Analysis 2 für Informatik UE (Müllner)
- Analysis 2 für Informatik UE (Panholzer)
- Analysis 2 für Informatik VO (Müllner)
- Analysis 2 für Informatik VO (Panholzer)
- Applied Deep Learning VU (Pacha)
- Ausgewählte Kapitel digitaler Forensik I VU (Grechenig)
- Bayes-Statistik UE UE (Felsenstein)
- Bayes-Statistik VO (Felsenstein)
- Business Intelligence VU (Tjoa)
- CTF Contests Einführung und Vertiefung in die "Olympiade" der IT Security Kultur durch OlympionikInnen UE (Grechenig)
- Cases in Engineering Connected Car IT Systems PR (Grechenig)
- Computational Social Science VU (Hanbury)
- Computer Vision Seminar für DiplomandInnen SE (Sablatnig)
- Crypto Asset Analytics VU (Haslhofer)
- Data Acquisition and Survey Methods VU (Nordhausen)
- Data-intensive Computing VU (Knees)
- Data-intensive Computing VU (Winkler)
- Datenmodellierung 2 VU (Fichte)
- Deep Learning for Visual Computing VU (Kampel)
- Didaktik in der Informatik Abenteuer Informatik SE (Futschek)
- Digitale Kompetenzen in der Lehre für Tutor innen VU (Matyas)
- Echtzeit-Visualisierung VU (Kovacs)
- Echtzeit-Visualisierung VU (Purgathofer)
- Echtzeit-Visualisierung VU (Raidou)
- Einführung in Semantic Systems VU (Ekaputra)
- Einführung in Semantic Systems VU (Sabou)
- Einführung in Semantic Systems VU (Tjoa)
- Einführung in das wissenschaftliche Schreiben VU (Matyas)
- Energy-efficient Distributed Systems VU (Brandic)
- Experiment Design for Data Science VU (Knees)
- Fokus Raumrelevantes Recht - Wasserrecht VO (List)
- Formale Methoden der Informatik UE (Lackner)
- Forschungsmethoden VU (Grechenig)
- Free Libre and Open Source Software VU (Raab)
- Free/Libre and Open Source Software VU (Raab)
- Gestaltung und Evaluation von Visualisierungen UE (Pohl)
- Interdisciplinary Project in Data Science PR (Eidenberger)
- Interdisciplinary Project in Data Science PR (Rauber)
- Introduction into Connected Car IT VU (Grechenig)
- Introduction to the Coq proof assistant VU (Ciabattoni)
- Kommunikation und Moderation VU (Pohl)
- Kommunikationstechnik SE (Dustdar)
- Lernergebnisorientierte Beschreibungen von Modulen SE (Freund)
- Machine Learning Algorithms and Applications PR (Eidenberger)
- Machine Learning Theory Project PR (Gärtner)
- Mathematical Programming VU (Brandstätter)
- Mathematical Programming VU (Ruthmair)
- Medizinische Bildverarbeitung VO (Langs)
- Metaheuristics and Hybrid Methods for Combinatorial Optimization VU (Raidl)
- Methodisches industrielles Software-Engineering mit Funktionalen Sprachen am Fallbeispiel Haskell VU (Grechenig)
- Mikrocomputer für Informatiker innen LU (Hauer)
- Mikrocomputer für Informatiker innen VU (Hauer)
- Mit der Kamera erzählen – Storytelling und Filmgestaltung VU (Fiala)
- Mobile (App) Prototyping and Evaluation PR (Eidenberger)
- Mobile (App) Software Engineering VU (Grechenig)
- Mobile App Software Engineering VU (Grechenig)
- Mobile Security VU (Grechenig)
- Modeling and Simulation VU (Popper)
- Optimierung von Legacy-Systemen - Lernen aus der Geschichte großer IT-Systeme und ihrer (Nicht-)Ablöse VU (Grechenig)
- Optimierung von Legacy-Systemen - Lernen aus der Geschichte großer IT-Systeme und ihrer Nicht-Ablöse VU (Grechenig)
- Pilots in Mobile Interaction User-centered Interaction Research and Evaluation VU (Grechenig)
- Pragmatische Werkzeuge für modernes Projektmanagement für Ingenieure VU (Grechenig)
- Presentation and Interaction in MOOCs PR (Purgathofer)
- Privatissimum aus Fachdidaktik Informatik PV (Freund)
- Privatissimum aus Fachdidaktik Informatik SE (Freund)
- Produktentwicklung am Beispiel Roboter VU (Lammer)
- ProgPro Together UE (Murzek)
- Programmierung von Strategie-Spielen - Strategische Planung und Reinforcement Learning VU (Eidenberger)
- Recommender Systems VU (Sacharidis)
- Runtime Verification VU (Bartocci)
- Semantic Web Technologies VU (Ortiz de la Fuente)
- Seminar für Diplomand innen für Data Science SE (Huemer)
- Seminar für DiplomandInnen SE (Träff)
- Seminar zu theoretischen Aspekten des Maschinellen Lernens SE (Gärtner)
- Soziale Kompetenz für Tutor innen SE (Dabringer)
- Sport-Technologien Einführung in den Mess- Trainings- und Plattform-Systembau für Athletinnen und Athleten VU (Grechenig)
- Structural Decompositions and Algorithms VU (Slivovsky)
- TechTalks - Industrielle digitale Technologien Stand 2021 PV (Grechenig)
- TechTalks - Industrielle digitale Technologien Stand 2022 PV (Grechenig)
- Technical and Organizational Mechanisms of Payments VU (Grechenig)
- Technik für Menschen Kollaboratives Arbeiten im Rahmen der Sustainable Development Goals VU (Herbig)
- Technik für Menschen Virtual Models and Scientific Value VU (Döring-Williams)
- Theorie und Praxis der Evaluierung von innovativen User Interfaces SE (Grechenig)
- Unkonventionelle IT (U.IT) zwischen (Kontroll-)Theorie Neuralen Netzen Quantenalgorithmen und -kryptographie SE (Grechenig)
- Unkonventionelle IT U.IT zwischen Kontroll-Theorie Neuralen Netzen Quantenalgorithmen und -kryptographie SE (Grechenig)
- Vertrags- und Haftungsrecht VU (Dillinger)
- Visualisierung 2 VU (Gröller)
- Werte als Führungselemente VU (Dorn)
- Wissenschaftliche Methodik SE (Ertl)
- Ökologische Aspekte beim Planen und Bauen SE (Linzer)
- Ökologische und gesellschaftliche Aspekte d Chemie VO (Grothe)
- Ökonomie der Aufmerksamkeit VO (Franck-Oberaspach)