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Informatics 2

Module name (EN):
Name of module in study programme. It should be precise and clear.
Informatics 2
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Production Informatics, Bachelor, ASPO 01.10.2023
Module code: PRI-INF2
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P222-0017
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
2V+2U (4 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
5
Semester: 2
Mandatory course: yes
Language of instruction:
German
Assessment:
Written exam

[updated 19.02.2018]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

KIB-INF2 (P222-0017) Computer Science and Communication Systems, Bachelor, ASPO 01.10.2021 , semester 2, mandatory course
KIB-INF2 (P222-0017) Computer Science and Communication Systems, Bachelor, ASPO 01.10.2022 , semester 2, mandatory course
PRI-INF2 (P222-0017) Production Informatics, Bachelor, ASPO 01.10.2023 , semester 2, mandatory course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
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):
None.
Recommended as prerequisite for:
Module coordinator:
Prof. Dr. Damian Weber
Lecturer: Prof. Dr. Damian Weber

[updated 07.08.2019]
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 2024 
[Sat Nov 23 09:12:29 CET 2024, CKEY=ki2, BKEY=pri, CID=PRI-INF2, LANGUAGE=en, DATE=23.11.2024]