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Curriculum

Modul CS4000-KP06, CS4000SJ14

Algorithmics (ALG14)

Duration:


1 Semester
Turnus of offer:


each winter semester
Credit points:


6
Course of studies, specific field and terms:
  • Master Computer Science 2019 (compulsory), Canonical Specialization Data Science and AI, Arbitrary semester
  • Master Computer Science 2019 (compulsory), Canonical Specialization Bioinformatics and Systems Biology, Arbitrary semester
  • Master Entrepreneurship in Digital Technologies 2020 (advanced module), technology field computer science, Arbitrary semester
  • Master Computer Science 2019 (basic module), Theoretical computer science, 1st or 2nd semester
  • Master Medical Informatics 2019 (optional subject), Theoretical computer science, 1st or 2nd semester
  • Master IT-Security 2019 (compulsory), Theoretical computer science, 1st or 2nd semester
  • Master Medical Informatics 2014 (basic module), computer science, 1st or 2nd semester
  • Master Entrepreneurship in Digital Technologies 2014 (basic module), technology field computer science, 1st or 2nd semester
  • Master Computer Science 2014 (optional subject), specialization field IT security and safety, 2nd or 3rd semester
  • Master Computer Science 2014 (basic module), Theoretical computer science, 1st or 2nd semester
Classes and lectures:
  • Algorithmics (lecture, 2 SWS)
  • Algorithmics (exercise, 2 SWS)
Workload:
  • 60 Hours in-classroom work
  • 100 Hours private studies and exercises
  • 20 Hours exam preparation
Contents of teaching:
  • complexity analysis of algorithmic problems
  • discrete optimization problems, linear programming
  • satisfiability and constraint satisfaction problems
  • randomized algorithms
  • approximation algorithms and heuristics
  • algorithms for algebraic problems
Qualification-goals/Competencies:
  • The students can model real problems in an algorithmic manner.
  • They can apply basic algorithmic techniques with full command.
  • They can analyze algorithms, in particular with respect to corrrectness and complexity.
  • They can design efficient algorithms for complex problems.
Grading through:
  • written exam
Requires:
Responsible for this module:
Teachers:
Literature:
  • Aho, Hopcroft, Ullman: Design and Analysis of Computer Algorithms - Addison Wesley, 1978
  • Cormen, Leiserson, Rivest, Stein: Introduction to Algorithms - The MIT Press, 2009
  • Mitzenmacher, Upfal: Probability and Computing - Cambridge University Press, 2005
  • Kreher, Stinson: Combinatorial Algorithms - CRC Press, 1999
  • Williamson, Shmoys: The Design of Approximation Algorithms - Cambridge University Press, 2011
Language:
  • German and English skills required
Notes:

Admission requirements for taking the module:
- None (the competencies of the modules listed under

Letzte Änderung:
1.2.2022