Data & Analytics 2: Mathematics for Computer Science
Niveau
Bachelor's program
Learning outcomes of the courses/module
The participants:
• can describe logical operators and apply them to simple tasks
• can describe set operators and apply them to simple tasks
• can describe mathematical relations and apply them to simple tasks
• can describe positional numeral systems (especially binary and decimal) and apply them to simple tasks
• can describe O-notation and apply it to simple tasks
• can describe number sequences and apply them to simple tasks
• can describe logical operators and apply them to simple tasks
• can describe set operators and apply them to simple tasks
• can describe mathematical relations and apply them to simple tasks
• can describe positional numeral systems (especially binary and decimal) and apply them to simple tasks
• can describe O-notation and apply it to simple tasks
• can describe number sequences and apply them to simple tasks
Prerequisites for the course
none
Course content
- Propositional logic and logical operators, predicate logic, arithmetic laws of propositional and predicate logic
- Set theory: basic concepts, set operators, calculation rules for sets
- Relations: basic concepts, properties of relations, equivalence and order relations
- Number concepts: sets of numbers, summation and product notation, positional numeral systems, binary and hexadecimal systems
- Sequences: concept of sequences, essential properties, convergence, O-notation
- Modular arithmetic: concept and calculation rules, applications
- Set theory: basic concepts, set operators, calculation rules for sets
- Relations: basic concepts, properties of relations, equivalence and order relations
- Number concepts: sets of numbers, summation and product notation, positional numeral systems, binary and hexadecimal systems
- Sequences: concept of sequences, essential properties, convergence, O-notation
- Modular arithmetic: concept and calculation rules, applications
Recommended specialist literature
- Brill, Manfred: Mathematik für Informatiker: Einführung an praktischen Beispielen aus der Welt der Computer. 2. Auflage, München, Wien, Carl Hanser Verlag, 2005.
- Nehrlich, Werner: Diskrete Mathematik: Basiswissen für Informatiker. München, Wien, Carl Hanser Verlag, 2003.
- Schwarze, Jochen. Mathematik für Wirtschaftswissenschaftler: Band 1: Grundlagen. 14. Auflage, Herne, NWB Verlag, 2015.
- Teschl, Gerald; Teschl, Susanne: Mathematik für Informatiker: Band 1: Diskrete Mathematik und Lineare Algebra. 4. Auflage, Berlin, Heidelberg, Springer Vieweg, 2013.
- Nehrlich, Werner: Diskrete Mathematik: Basiswissen für Informatiker. München, Wien, Carl Hanser Verlag, 2003.
- Schwarze, Jochen. Mathematik für Wirtschaftswissenschaftler: Band 1: Grundlagen. 14. Auflage, Herne, NWB Verlag, 2015.
- Teschl, Gerald; Teschl, Susanne: Mathematik für Informatiker: Band 1: Diskrete Mathematik und Lineare Algebra. 4. Auflage, Berlin, Heidelberg, Springer Vieweg, 2013.
Assessment methods and criteria
Portfolio exam
Language
German
Number of ECTS credits awarded
6
Semester hours per week
Planned teaching and learning method
Lecture, tutorials, group work
Semester/trimester in which the course/module is offered
1