Modul
Algorithms II [M-INFO-101173]
Credits
6Recurrence
Jedes WintersemesterDuration
1 SemesterLanguage
German/EnglishLevel
3Version
1Responsible
- Prof. Dr. Hartmut Prautzsch
- Prof. Dr. Dorothea Wagner
- Prof. Dr. Peter Sanders
- Prof. Dr. Hartmut Prautzsch
- Prof. Dr. Dorothea Wagner
- Prof. Dr. Peter Sanders
- Prof. Dr. Hartmut Prautzsch
- Prof. Dr. Dorothea Wagner
- Prof. Dr. Peter Sanders
- Prof. Dr. Hartmut Prautzsch
- Prof. Dr. Dorothea Wagner
- Prof. Dr. Peter Sanders
Organisation
- KIT-Fakultät für Informatik
Part of
Bricks
Identifier | Name | LP |
---|---|---|
T-INFO-102020 | Algorithms II | 6 |
Competence Certificate
See partial achievements (Teilleistung)
Competence Goal
The student has an in-depth insight into the theoretical and practical aspects of algorithms and is able to identify and formally formulate algorithmic problems in various application areas. Furthermore, they know advanced algorithms and data structures from the areas of graph algorithms, algorithmic geometry, string matching, algebraic algorithms, combinatorial optimization, and external memory algorithms. They are able to independently understand algorithms they are unfamiliar with, associate them with the above areas, apply them, determine their running time, evaluate them, and select appropriate algorithms for given applications. Furthermore, the student is able to adapt existing algorithms to related problems. In addition to algorithms for concrete problems, the student knows advanced techniques of algorithmic design. This includes parameterized algorithms, approximation algorithms, online algorithms, randomized algorithms, parallel algorithms, linear programming, and algorithm engineering techniques. For given algorithms, the student is able to identify techniques used to better understand these algorithms. In addition, they are able to select appropriate techniques for a given problem and use them to design their own algorithms.
Prerequisites
See partial achievements (Teilleistung)
Content
This module is designed to provide students with the basic theoretical and practical aspects of algorithm design, analysis, and engineering. It teaches general methods for designing and analyzing algorithms for basic algorithmic problems, as well as the basic principles of general algorithmic methods such as approximation algorithms, linear programming, randomized algorithms, parallel algorithms, and parameterized algorithms.
Workload
Lecture with 3 semester hours + 1 semester hour exercise
6 ECTS correspond to about 180 hours
about 45h visiting the lectures
about 15h visiting the exercises
about 90h follow-up of lectures and solving the exercise sheets
about 30h preparation for the exam