| Duration: 
 1 Semester
 | Turnus of offer: 
 each summer semester
 | Credit points: 
 8
 | 
  |  Course of studies, specific field and terms:Bachelor CLS 2023 (compulsory), foundations of computer science, 2nd semesterBachelor MES 2020 (optional subject), computer science / electrical engineering, 3rd semester at the earliestBachelor Media Informatics 2020 (compulsory), computer science, 2nd semesterBachelor Computer Science 2019 (compulsory: aptitude test), foundations of computer science, 2nd semesterBachelor Robotics and Autonomous Systems 2020 (compulsory), computer science, 2nd semesterBachelor Medical Informatics 2019 (compulsory), computer science, 2nd semesterBachelor Computer Science 2016 (compulsory: aptitude test), foundations of computer science, 2nd semesterBachelor CLS 2016 (compulsory), foundations of computer science, 2nd semesterBachelor Robotics and Autonomous Systems 2016 (compulsory), computer science, 2nd semesterBachelor IT-Security 2016 (compulsory: aptitude test), computer science, 2nd semesterBachelor Medical Informatics 2014 (compulsory), computer science, 2nd semesterBachelor MES 2014 (optional subject), computer science / electrical engineering, 4th or 6th semesterBachelor Media Informatics 2014 (compulsory), foundations of computer science, 2nd semesterBachelor Computer Science 2014 (compulsory: aptitude test), foundations of computer science, 2nd semesterBachelor Medical Informatics 2011 (compulsory), computer science, 2nd semesterBachelor MES 2011 (compulsory), foundations of computer science, 4th semesterBachelor CLS 2010 (compulsory), foundations of computer science, 2nd semesterBachelor Computer Science 2012 (compulsory: aptitude test), foundations of computer science, 2nd semester
 | 
  |   |  Classes and lectures:  Algorithms and Data Structures (exercise, 2 SWS)Algorithms and Data Structures (lecture, 4 SWS) |  Workload:  90 Hours in-classroom work125 Hours private studies25 Hours exam preparation |  | 
  |   |  Contents of teaching:  |   |  Sorting, algorithm analysis, heapsDistribution sortPriority queuesSetsSetsSets of stringsDisjoint setsAssociating objectsGraphsSearch graph for game playingDynamic Programming principle, greedy algorithmsOptimization problems, sequence alignment (longest common subsequence), knapsack problem, planning and layout problems, determining change coins, notion of completeness of algorithmsString matchingHard problemsPruning and subgraph isomorphismApproximation |  | 
  |  Qualification-goals/Competencies:  The students can explain the central ideas, define the relevant concepts and explain the functioning of algorithms with help of application scenarios for all the items listed in contents of teaching. | 
  |  Grading through:  | 
  |  Is requisite for:  | 
  |  Requires:  | 
  |  Responsible for this module:  Teachers:  | 
  | Literature: Thomas H. Cormen, Charles E. Leiserson, Ronald Rivest, Clifford Stein: Algorithmen - Eine Einführung - Oldenbourg Verlag, 2013 | 
  |  Language: | 
  |  Notes:Admission requirements for taking the module:- None (The competencies of the modules listed under 'Requires' are needed for this module, but are not a formal prerequisite.)
 
 Admission requirements for participation in module examination(s):
 - Successful completion of exercise sheets as specified at the beginning of the semester.
 
 Module exam(s):
 - CS1001-L1: Algorithms and Data Structures, written exam, 90min, 100% of the module grade.
 | 
  | Letzte Änderung:25.7.2025 | 
 
 
	
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