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Informatics 1

Module name (EN): Informatics 1
Degree programme: Computer Science and Communication Systems, Bachelor, ASPO 01.10.2017
Module code: KIB-INF1
Hours per semester week / Teaching method: 2V+2U (4 hours per week)
ECTS credits: 5
Semester: 1
Mandatory course: yes
Language of instruction:
German
Assessment:
Written exam
Curricular relevance:
KIB-INF1 Computer Science and Communication Systems, Bachelor, ASPO 01.10.2017, semester 1, 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):
None.
Recommended as prerequisite for:
KIB-INF2 Informatics 2
KIB-RN Computer Networks
KIB-SDSA Simulation of Discrete Systems with AnyLogic


[updated 12.01.2018]
Module coordinator:
Prof. Dr. Damian Weber
Lecturer:
Dipl.-Inform. Marion Bohr (exercise)
Sarah Theobald, M.Sc. (exercise)


[updated 05.12.2019]
Learning outcomes:
After successfully completing this course, students will be able to use the basic concepts of algorithms and data structures in a targeted manner.
They will understand the representation of data in a computer and can use it in data structures to solve problems. Through the use of a Random Access Machine machine model they will gain become acquainted with the basic operations a computer can perform. They will be able to accurately express problems and analyze simple algorithmic problems to develop solutions. They will be able to asymptotically estimate the effort required for the solution.
  
The related techniques will be learned and intensified in theoretical training sessions by means of independent work.

[updated 19.02.2018]
Module content:
1. Mathematic principles
1.1 Number systems
1.2 Boolean algebra
  
2. Random Access Machine machine model
2.1 Structure
2.2 Program correctness
2.3 Program runtime
 
3. Data structures
3.1 Arrays
3.2 Lists
3.3 Heaps
3.4 Hash tables
3.5 Search trees
 
4. Algorithms
4.1 High-level programming languages
4.2 Recursion
4.3 Sorting
 

[updated 19.02.2018]
Teaching methods/Media:
RAMses, a RAM simulator

[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:
WS 2019/20, WS 2018/19, WS 2017/18
[Wed Jan 22 12:14:05 CET 2020, CKEY=ki1a, BKEY=ki2, CID=KIB-INF1, LANGUAGE=en, DATE=22.01.2020]