Lecture: 2.01.536 Convolutional Neural Networks - Details

General information

Course name	Lecture: 2.01.536 Convolutional Neural Networks
Subtitle	inf536
Course number	2.01.536
Semester	SoSe2023
Current number of participants	108
expected number of participants	100
Home institute	Department of Computing Science
Courses type	Lecture in category Teaching
First date	Monday, 04.09.2023 08:00 - 18:00, Room: V03 0-D002
Type/Form	V+Ü Blockveranstaltung
Lehrsprache	englisch

Lecturers

• Prof. Dr. Oliver Kramer

Rooms and times

V03 0-D002

Monday, 04.09.2023 - Friday, 08.09.2023, Monday, 11.09.2023 - Friday, 15.09.2023 08:00 - 18:00

A14 1-101 (Hörsaal 1)

Wednesday, 27.09.2023 08:00 - 10:00

A14 1-102 (Hörsaal 2)

Wednesday, 27.09.2023 08:00 - 10:00

A14 1-103 (Hörsaal 3)

Friday, 03.11.2023 10:00 - 12:00

Module assignments

• Campusmanagementsystem Stud.IP
  • Business Informatics - Master's Programme
    • Akzentsetzungsmodule der Informatik
      • inf536 - Computational Intelligence II
        • Exercises
        • Lecture
  • Engineering of Socio-Technical Systems - Master's Programme
    • Systems Engineering
      • inf536 - Computational Intelligence II
        • Exercises
        • Lecture
    • Human-Computer Interaction
      • inf536 - Computational Intelligence II
        • Exercises
        • Lecture
    • Embedded Brain Computer Interaction
      • inf536 - Computational Intelligence II
        • Exercises
        • Lecture
  • Environmental Modelling - Master's Programme
    • Mastermodule
      • inf536 - Computational Intelligence II
        • Exercises
        • Lecture
  • Applied Economics and Data Science - Master-Studiengang
    • Data Science
      • inf536 - Computational Intelligence II
        • Exercises
        • Lecture
  • Computing Science - Master's Programme
    • Angewandte Informatik
      • inf536 - Computational Intelligence II
        • Exercises
        • Lecture

Admission settings

The course is part of admission "Anmeldung gesperrt (global)".

Erzeugt durch den Stud.IP-Support
The following rules apply for the admission:

• Admission locked.