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Computer Science 1 - Review Course

Module name (EN):
Name of module in study programme. It should be precise and clear.
Computer Science 1 - Review Course
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Applied Informatics, Bachelor, ASPO 01.10.2022
Module code: PIB-IREP1
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.
-
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
0
Semester: 1
Mandatory course: no
Language of instruction:
German
Assessment:
 


[updated 29.04.2024]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

PIB-IREP1 Applied Informatics, Bachelor, ASPO 01.10.2022 , semester 1, optional course
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
Module coordinator:
Prof. Dr. Klaus Berberich
Lecturer:
Moritz Niederer, M.Sc.


[updated 09.04.2024]
Learning outcomes:
After successfully completing this module, students will be able to formulate and analyze algorithms for solving simple problems. They will understand how numbers and characters are represented in a computer. They will be capable of converting between and computing in the underlying numeral systems. Students will be familiar with the basic concepts and rules of predictive logic and can apply them to determine the equivalence of two expressions. On the basis of the machine model Random Access Machine (RAM), students will learn the basic operations of a computer. They will be able to implement simple programs with the RAM commands, prove their correctness and determine their time and space complexity. Students will become familiar with basic algorithms (e. g. for searching and sorting) and will be able to combine them like building blocks to solve more complex problems. Based on these fundamental algorithms, students will be able to understand important solution strategies (e. g. divide and conquer algorithm, recursion and dynamic programming). Students will also learn about elementary data structures (e. g. linked lists and binary heaps) and will be able to use them appropriately depending on the situation.

[updated 29.04.2024]
Module content:
1. Introduction
  
2. Mathematical principles
2.1 Number systems
2.2 Boolean algebra
  
3. RAM as a machine model
3.1 Components
3.2 Program correctness
3.3 Program runtime
  
4. Algorithms
4.1 Pseudocode from a high-level programming language
4.2 Searching
4.3 Sorting
  
5. Data structures
5.1 Dynamic arrays
5.2 Linked lists
5.3 Binary heaps
5.4 Binary search trees
5.5 Hash tables

[updated 29.04.2024]
Recommended or required reading:
Cormen Thomas H., Leiserson Charles E., Rivest Ronald L. und Stein Clifford: Algorithmen - Eine Einführung, Oldenbourg , 2013
  
Gumm Hans-Peter und Sommer Manfred: Einführung in die Informatik, Oldenbourg Verlag, 2012
  
Sedgewick Robert und Wayne Kevin: Algorithmen und Datenstrukturen, Pearson Studium, 2014

[updated 29.04.2024]
 
[Wed Oct 30 09:27:53 CET 2024, CKEY=pi1r, BKEY=pi2, CID=PIB-IREP1, LANGUAGE=en, DATE=30.10.2024]