| 03-IMVA-3DMFT | 3D Modelling with FabLab Technologies (in English) You can find course dates and further information in Stud.IP. | Dr. Bernhard Robben Michael Lund |
| 03-IMVP-ACA | Advanced Computer Architecture (in English) You can find course dates and further information in Stud.IP. | Prof. Dr. Rolf Drechsler Dr. Kamalika Datta |
| 03-IMAP-ACG | Advanced Computer Graphics (in English) You can find course dates and further information in Stud.IP. | Prof. Dr. Gabriel Zachmann |
| 03-IMVA-ACSS | Applied Computer Science in Sports (in English) Schwerpunkt: IMVA-AI, IMVA-DMI
https://lvb.informatik.uni-bremen.de/imva/03-imva-acss.pdf
The aim of this course is to create an understanding of the major aspects of sports applications. The course is split into two parts: the first half has a classic lecture/tutorial style, whereas the second half will focus on the creation of individual sports applications.
The lectures will explain the necessary fundamentals, such as sensor technology, user feedback, and the conduction of empirical studies, along with a number of inspiring examples.
In the project part, own prototypes for sports applications are developed in small groups. The exact application as well as the technical implementation approach can be chosen freely. The final graded outcome of the course will be a small sports application about which a presentation has to be held and a documentation in a scientific paper style has to be written.
The course will be held in English.
Schwerpunkt: AI, DMI | Robert Porzel Dr. Tim Laue Bastian Dänekas |
| 03-IMAT-APX | Approximation Algorithms (in English) Profil: SQ, KIKR.
Schwerpunkt: IMA-SQ, IMVT-AI, IMVT-VMC
weitere Studiengänge: M-M-Alg-Num, M-T
https://lvb.informatik.uni-bremen.de/imat/03-imat-apx.pdf
A large number of problems arising in practical scenarios like communication, transportation, planning, logistics etc. can be modeled as combinatorial optimization problems. In most cases, these problems are computationally intractable and one often resorts to heuristics that provide sufficiently good solutions in reasonable amount of runtime. However, in most cases, such heuristics do not provide a worst case guarantee on the performance in comparison to the optimum solution. In this course, we shall study algorithms for combinatorial optimization problems which can provide strong mathematical guarantees on performance. The course aims at developing a toolkit for solving such problems. The lectures will consist of designing polynomial-time algorithms and proving rigorous bounds on their worst case performances.
We review many classical results in the field of approximation algorithms, highlighting different techniques commonly used for the design of such algorithms. Among others, we will treat the following topics:
• Greedy algorithms and Local Search
• Rounding Data and Dynamic Programming
• Deterministic Rounding of Linear Programs (LPs)
• Random Sampling and Randomized Rounding of LPs
• Primal-Dual Methods
• Hardness of Approximation
• Problem Solving under Uncertainty | Prof. Dr. Nicole Megow Dr. Alexander Lindermayr |
| 03-IMVT-CGEOM | Computational Geometry (in English) Profil: KIKR, DMI.
Schwerpunkt: IMVT-AI, IMVT-DMI, IMVT-VMC
https://lvb.informatik.uni-bremen.de/imvt/03-imvt-cgeom.pdf
Die Veranstaltung beginnt am 10.04.2025.
This course looks at a number of algorithms and data structures from computational geometry with a view on their application to computer graphics. You should feel comfortable with geometric-mathematical thinking as well as algorithmic thinking. We will not need, however, complex mathematics. Die Homepage zur Vorlesung befindet sich immer unter http://cgvr.cs.uni-bremen.de -> Teaching | Prof. Dr. Gabriel Zachmann |
| 03-IMVA-DSS | Decision Support Systems (in English) You can find course dates and further information in Stud.IP. | Dr. Marc Wyszynski Prof. Dr. Dr. Björn Niehaves Sebastian Weber Jan Westermann Patricia Zauchner, Ph.D. |
| 03-IMAP-DIS | Design of Information Systems (in English) You can find course dates and further information in Stud.IP. | Martin Gogolla |
| 03-IMVA-EI | Embodied Interaction (in English) You can find course dates and further information in Stud.IP. | Robert Porzel Prof. Dr. Rainer Malaka |
| 03-IMAA-EC | Entertainment Computing (in English) You can find course dates and further information in Stud.IP. | Prof. Dr. Rainer Malaka Rachel Ringe Leon Tristan Dratzidis Nima Zargham |
| 03-IMVP-WAWR | AI - Knowledge Acquisition and Knowledge Representation (in English) You can find course dates and further information in Stud.IP. | Michael Beetz Oger aus Weit Weit Weg Tom Schierenbeck, ????????? |
| 03-IMAP-LLML | Life-Long Machine Learning (in English) You can find course dates and further information in Stud.IP. | Martin Mundt |
| 03-IMAA-MAD | Mobile App Development (in English) Profil: DMI
Schwerpunkt: IMA-DMI, IMVA-DMI
https://lvb.informatik.uni-bremen.de/imva/03-imva-mad.pdf
Die Veranstaltung richtet sich an Studenten der Informatik und Digitalen Medien. In Gruppenarbeit sollen die Studierenden semesterbegleitend ein App-Projekt umsetzen. In der Vorlesung werden alle relevanten Informationen der modernen Softwareentwicklung, mit Fokus auf die mobile App-Entwickung, vermittelt. Dazu gehören Themen wie mobiles Testing, Scrum, UX Design, Evaluation & Nutzertests, Design Patterns und Cross-Plattform-Entwicklung. Das Ziel dabei ist die Vermittlung von praxisrelevantem Wissen aus dem Alltag eines erfolgreichen Unternehmens. | Prof. Dr. Rainer Malaka David Ruh Nicolas Autzen Marcus-Sebastian Schröder |
| 03-IMVP-PROSY | Program Synthesis (in English) You can find course dates and further information in Stud.IP. | Mario Gleirscher |
| 03-IMAP-QSE | Quality oriented system design (in English) You can find course dates and further information in Stud.IP. | Prof. Dr. Rolf Drechsler |
| 03-IMAP-RL | Reinforcement Learning (in English) You can find course dates and further information in Stud.IP. | Frank Kirchner Melvin Laux |
| 03-IMVP-RPROS | Robot Programming with ROS (in English) IMVP-AI
Room: TAB Knowledge (0.30)
Learning Outcome:
* Understand and apply concepts of functional programming
* Understand and apply artificial intelligence techniques
* (…) IMVP-AI
Room: TAB Knowledge (0.30)
Learning Outcome:
* Understand and apply concepts of functional programming
* Understand and apply artificial intelligence techniques
* Program an autonomous robot platform using ROS
* Implement failure handling techniques
Contents:
This course gives a solid practical introduction to the Robot Operating System (ROS2) up to advanced topics on how to control robots.
The lecture covers the tools of ROS2 and the cognitive robot architecture CRAM.
Students work in small groups on a TurtleBot to apply the lectures content hands-on to the robot.
Eventually the students will be able to design an autonomously driving vehicle, being evaluated in a final competition.
Profile: KIKR
https://lvb.informatik.uni-bremen.de/imvp/03-imvp-rpros.pdf | Michael Beetz |
| 03-IMAP-SECORO | Software Engineering for Cognitive Robots (in English) You can find course dates and further information in Stud.IP. | Nico Hochgeschwender |
| 03-IMAP-UUW | Management of Uncertain Knowledge (in English) You can find course dates and further information in Stud.IP. | Kerstin Schill Joachim Clemens |
