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Informatics 2

Module name (EN): Informatics 2
Degree programme: Computer Science and Communication Systems, Bachelor, ASPO 01.10.2017
Module code: KIB-INF2
Hours per semester week / Teaching method: 2V+2U (4 hours per week)
ECTS credits: 5
Semester: 2
Mandatory course: yes
Language of instruction:
German
Assessment:
Written exam
Curricular relevance:
KIB-INF2 Computer Science and Communication Systems, Bachelor, ASPO 01.10.2017, semester 2, mandatory course
Workload:
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 150 hours (equivalent to 5 ECTS credits).
There are therefore 105 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
KIB-INF1 Informatics 1
KIB-MAT1 Mathematics 1


[updated 12.01.2018]
Recommended as prerequisite for:
KIB-RN Computer Networks
KIB-SDSA Simulation of Discrete Systems with AnyLogic


[updated 17.11.2016]
Module coordinator:
Prof. Dr. Damian Weber
Lecturer:
Dipl.-Inform. Marion Bohr (exercise)
Thorsten Jakobs, M.Sc. (exercise)


[updated 12.01.2018]
Learning outcomes:
After successfully completing this course, students will understand the formulation of different algorithmic problems as a graph problem.
  
Students will be able to solve graph problems algorithmically. The knowledge about data structures and basic algorithmic techniques acquired in the course "Informatics 1" will be applied to solve these problems. In this way, students will acquire the skills required to analyze more complex algorithms.
  
Finally, an intuitive introduction to important complexity classes will provide the basis for understanding the algorithmic solvability of problems. The approaches of Greedy algorithms and dynamic programming will be understood as techniques for solving difficult algorithmic problems approximately and efficiently. By analyzing the consumption of resources, students will be able to decide for individual problems whether efficient, exact or heuristic procedures are available for solving them.


[updated 26.02.2018]
Module content:
1. Graphs
1.1 Data structures
1.2 Basic algorithms
1.3 Shortest paths
1.4 Connected components
 
2. Problem solving techniques
2.1 Dynamic programming
2.2 Greedy algorithms
2.3 Analytical techniques of approximate methods
 


[updated 19.02.2018]
Teaching methods/Media:
 


[updated 19.02.2018]
Recommended or required reading:
Cormen Th., Leiserson Ch., Rivest R., Introduction to Algorithms, Oldenbourg, 2013
Sedgewick R., Wayne K., Algorithmen und Datenstrukturen, Pearson Studium, 2014


[updated 19.02.2018]
Module offered in:
SS 2020, SS 2019, SS 2018
[Wed Jan 22 12:05:31 CET 2020, CKEY=ki2, BKEY=ki2, CID=KIB-INF2, LANGUAGE=en, DATE=22.01.2020]