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SoSe 2024

Bauhaus.Module: Applied AI Methods for Planning and Design - Einzelansicht

  • Funktionen:
  • Zur Zeit keine Belegung möglich
Veranstaltungsart Seminar SWS 4
Veranstaltungsnummer 123223302 Max. Teilnehmer/-innen 25
Semester WiSe 2023/24 Zugeordnetes Modul Bauhaus.Modul

Architektur, M.Sc. PO 2020
Wahlpflichtmodul - Architektur
Architektur, M.Sc. PO 18
Wahlpflichtmodul - Architektur
Architektur, M.Sc. PO 14
Wahlpflichtmodul - Architektur

Integrated Urban Design and Developpment, M.Sc. PO 2020
elective module
Integrated Urban Design and Developpment, M.Sc. PO 18
elective module

MediaArchitecture, M.Sc. PO 2022
Fachmodul - Digitale Planung
MediaArchitecture, M.Sc. PO 2020
Fachmodul - Digitale Planung
Erwartete Teilnehmer/-innen
Sprache deutsch
Termine Gruppe: [unbenannt]
  Tag Zeit Rhythmus Dauer Raum Raum-
Lehrperson Bemerkung fällt aus am Max. Teilnehmer/-innen
Einzeltermine anzeigen
Do. 15:15 bis 16:45 wöch. 12.10.2023 bis 01.02.2024  Belvederer Allee 1a - Allg. Medienpool 003      
Gruppe [unbenannt]:
Zur Zeit keine Belegung möglich

Zugeordnete Person
Zugeordnete Person Zuständigkeit
König, Reinhard, Prof., Dr.-Ing. verantwortlich
Abschluss Studiengang Semester Leistungspunkte
Master Architektur (M.Sc.), PV14 1 - 3 6
Master Architektur (M.Sc.), PV18 1 - 3 6
Master Integrated Urban Development and Design (M.Sc.), PV 18 1 - 3 6
Master MediaArchitecture (M.Sc.), PV2020 1 - 3 6
Master Integrated Urban Development and Design (M.Sc.), PV 2020 1 - 3 6
Master Architektur (M.Sc.), PV2020 1 - 3 6
Master MediaArchitecture (M.Sc.), PV2022 1 - 3 6
Leer Alle Studiengänge -
Zuordnung zu Einrichtungen
Computational Architecture

This course serves as an introduction to the practical implementation of deep learning models, focusing on real-world issues. The syllabus includes the exploration of data analysis and visualization, and computer vision, with an emphasis on generative models such as stable diffusion and large language models like ChatGPT.

We encourage students to collaborate in interdisciplinary teams to generate ideas about how, when, and for whom different algorithms can address specific problems in various domains. The course advances through multiple stages of idea presentation and pitching, with the ultimate aim being the development of a preliminary prototype and a compelling pitch by the end of the course.

By the end of this course, students will:

- Gain a better understanding of AI and deep learning models and how they function;

- Develop the ability to build applications using these models;

- Improve critical understanding of data and models, including when to use and when not to use different classes of algorithms.

The course will commence with a presentation of various deep learning and AI models, including a range of example use-cases and critical reflections on their usage. This is designed to inspire students' idea generation on how advanced AI models can be used to solve problems in their specific domains.

Students will then work in groups to develop ideas and build prototypes. Through multiple pitch rounds, these ideas will be refined and discussed collectively. Tutors will provide practical implementation assistance. The final course outcome will be a well-prepared pitch and a minimum viable product (MVP) prototype or mock-up of their project.

This course is open to master students and senior bachelor students. It is recommended that participants possess basic coding knowledge (particularly Python), be comfortable with software usage, be adept at problem-solving, and have a proactive, hands-on approach.


Join our "Applied AI Methods for Planning and Design" Bauhaus.Module this fall. Utopians will innovate for a better world, Dystopians will explore AI's dark side. Dive into data analysis, visualization, and AI tools. Learn, debate, develop, pitch your own AI application, and finally develop a first prototype. Open to master students and python enthusiasts. Expand your horizons in AI!


The course is open to all Bachelor, Master and PhD students of the faculties of Architecture and Urbanism, Civil Engineering, Art and Design, and Media as part of the ”Bauhaus.Modules”. Before registering, please consult your academic advisor and clarify whether this course can be credited to your curriculum. If required, you can conclude a learning agreement before the start of the course.

Keine Einordnung ins Vorlesungsverzeichnis vorhanden. Veranstaltung ist aus dem Semester WiSe 2023/24 , Aktuelles Semester: SoSe 2024

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