Technische Universität Wien (TU Wien)*

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The Technische Universität Wien (TU Wien or TUW; English: Vienna University of Technology), formerly the Technische Hochschule Wien and the k.k. Polytechnisches Institut, has offered the following Knowledge Management education and training opportunities:

Academy for Continuing Education (ACE)


Kompakt-Programme > Bereich Technology & Engineering

  • Data Science & Knowledge Management (Stand 2021: in Planung)

Fakultät für Informatik1)

Graduate Degrees/Programs

  • Master of Science Information & Knowledge Management** (Vertiefung: Knowledge Engineering)2)
      Basis – Allgemein
      VL Advanced Software Engineering (ab 2007: LU)
      VO Data Mining (bis 2008)
      VU Formale Methoden der Informatik (ab 2009: VO)
      VO Grundzüge der Artificial Intelligence
      VO Knowledge Management
      UE Knowledge Management (ab 2007)
      SE Seminar für DiplomandInnen
      VU Semistrukturierte Daten (ab 2007: VL)
      VU Wissensbasierte Systeme (ab 2007: V=)

      Basis – Knowledge Engineering
      VU Einführung in Semantic Web
      VU Machine Learning
      VU Problem Solving and Search in Artificial Intelligence

      Wahl – Allgemein
      PR Informatikpraktikum 1
      PR Informatikpraktikum 2

      Wahl – Knowledge Engineering
      VO Ausgewählte Kapitel aus Knowledge Management und Digital Media (ab 2009)
      VO Artificial Intelligence und Semantic Web (bis 2008)
      VO Logik für Wissensrepräsentation (ab 2007)
      UE Knowledge Management (bis 2008)
      VU Nichtmonotones Schließen
      VU Robotik
      VU Semi-Automatic Information and Knowledge Systems
      SE Seminar aus Artificial Intelligence
      SE Seminar aus Knowledge Management
      SE Seminar aus Logik (ab 2007)
      SE Seminar aus theoretischer Informatik und Logik (bis 2007)
      SE Seminar aus Theoretischer Informatik (ab 2007)
      VO Verarbeitung deklarativen Wissens
      VU Wissensbasiertes Planen

  • Dipl.-Ing. Magisterstudium Informatik (Schwerpunkt: Information & Knowledge Management; Vertiefungsfach: Knowledge Engineering (KE))**2)
      Basis – Allgemein
      VO Einführung in die AI
      VU Formale Methoden der Informatik
      VO Knowledge Management
      VO Maschinelles Lernen und Data Mining
      SE Seminar für DiplomandInnen
      VU Semistrukturierte Daten 1
      VL Software Engineering 2
      VO Wissensbasierte Systeme

      Basis – Knowledge Engineering
      VU Fortgeschrittene Methoden des maschinellen Lernens
      VO Logik für Wissensrepräsentation
      VO Neural Computation 1

      Wahl – Allgemein
      PR Praktikum aus Knowledge Engineering

      Wahl – Knowledge Engineering
      VU AK aus Knowledge Engineering 1
      VU AK aus Knowledge Engineering 2
      VU Constraint Solving
      VU Heuristische Optimierungsverfahren
      UE Knowledge Management
      VU Komplexitätstheorie
      LU Neural Computation 1
      VU Nichtmonotones Schließen
      VU Nichtmonotones Schlieen
      VU Robotik
      VO Verarbeitung deklarativen Wissens

Institute of Logic and Computation > Knowledge-Based Systems Research Unit3)

  • PhD in Informatics (research area: Knowledge-Based Systems)


Institut für Visual Computing & Human-Centered Technology > Forschungsbereich Multidisciplinary Design & User Research

  • 11th European Conference on Computer-Supported Cooperative Work (ECSCW 2009), 7-11 September 2009, Vienna, Austria

Institute of Logic and Computation > Knowledge-Based Systems Research Unit3)

  • 14th International Conference on the Principles of Knowledge Representation & Reasoning (KR 2014), July 20-24, 2014, Vienna University of Technology, Vienna, Austria
    (Co-host: Database and Artificial Intelligence Group, Institute of Logic and Computation)


Database and Artificial Intelligence Group

  • Foundational Challenges in Data and Knowledge Management, March 25, 2018, TU Vienna, Vienna, Austria
    (Georg Gottlob Special Event; co-located with EDBT/ICDT Joint Conference, Mar 26-29)

      Human-In-the-Loop Personalization
      What are the Limits for Efficient Conjunctive Query Evaluation in the Presence of Constraints?

      Abstraction vs. Performance in Database Systems
      On the Succinctness of Query Rewriting for Datalog+/-
      From Hypertree Width to Submodular Width and Data-dependent Structural Decompositions
      Algorithmic Metatheorems for Second-Order Logic
      The Quest for Definitive Results: Some Examples in Georg Gottlob’s Work

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