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This entry is from Winter semester 2019/20 and might be obsolete. You can find a current equivalent here.

CS 566 — Efficient Algorithms
(dt. Effiziente Algorithmen)

Level, degree of commitment Advanced module, depends on importing study program
Forms of teaching and learning,
Lecture (4 SWS), recitation class (2 SWS),
270 hours (90 h attendance, 180 h private study)
Credit points,
formal requirements
9 CP
Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises as well as at least 2 presentations of the tasks.
Examination type: Oral or written examination
The grading is done with 0 to 15 points according to the examination regulations for the degree program B.Sc. Data Science.
Subject, Origin Computer Science, B.Sc. Data Science
One semester,
Person in charge of the module's outline Prof. Dr. Bernhard Seeger


Algorithmic techniques

  • Greedy algorithms
  • Dynamic programming
  • Divide-and-conquer
  • space and time complexity (worst-case, amortised, output-sensitive, resolution of running time recurrences)
  • Correctness proofs
  • Algorithms for set problems, graph problems, text problems and geometric problems
  • Algorithms for external memory models
  • Algorithms for data streams
  • Approximation algorithms

Qualification Goals

  • Algorithm design skills,
  • Knowledge of the most important design and analysis paradigms,
  • Use of efficient data structures for the design of algorithms,
  • Insights into the analysis of algorithms with respect to correctness and efficiency
  • Practice of scientific methods (recognition, formulation, and solution of problems, training of abstract thinking),
  • Training of oral communication skills in the exercises by practicing free speech in front of an audience and during discussion.


None. The competences taught in the following modules are recommended: either Algorithms and Data Structures or Practical Informatics II: Data Structures and Algorithms for Pre-Service-Teachers.

Recommended Reading

  • Cormen, Leierson, Rivest, Stein: Algorithmen - Eine Einführung. Oldenbourg.
  • Ottmann, Widmayer: Algorithmen und Datenstrukturen. Spektrum Akad. Verlag.
  • Schöning: Algorithmik. Spektrum Akad. Verlag. 2001.
  • Güting, Dieker: Datenstrukturen und Algorithmen, Vieweg+Teubner

Please note:

This page describes a module according to the latest valid module guide in Winter semester 2019/20. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.