Data & Analytics 2: Mathematics for Computer Science
Niveau
Bachelor
Learning outcomes of the courses/module
The students
- understand logical operators and can apply them in simple tasks
- understand set operators and can apply them in simple tasks
- understand mathematical relations and can apply them in simple tasks
- understand place value systems (especially binary and decimal) and can apply them in simple tasks
- understand O-notation and can apply it in simple tasks
- understand number sequences and can apply them in simple tasks
- understand logical operators and can apply them in simple tasks
- understand set operators and can apply them in simple tasks
- understand mathematical relations and can apply them in simple tasks
- understand place value systems (especially binary and decimal) and can apply them in simple tasks
- understand O-notation and can apply it in simple tasks
- understand number sequences and can apply them in 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, arithmetic rules for sets
- Relations: Basic concepts, properties of relations, equivalence, and ordering relations
- Number concepts: Sets of numbers, sum and product signs, place value systems, binary and hexadecimal systems
- Sequences: Concept of sequence, some essential properties, convergence, O-notation
- Modular arithmetic: concept and calculation rules, applications
- Set theory: basic concepts, set operators, arithmetic rules for sets
- Relations: Basic concepts, properties of relations, equivalence, and ordering relations
- Number concepts: Sets of numbers, sum and product signs, place value systems, binary and hexadecimal systems
- Sequences: Concept of sequence, some 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. 2nd edition, Munich, Vienna, Carl Hanser Publishing, 2005
- Nehrlich, Werner: Diskrete Mathematik: Basiswissen für Informatiker. Munich, Vienna, Carl Hanser
Publishing, 2003
- Schwarze, Jochen: Mathematik für Wirtschaftswissenschaftler. Band 1: Grundlagen. 14th edition, Herne, NWB Publishing, 2015
- Teschl, Gerald; Teschl, Susanne: Mathematik für Informatiker. Band 1: Diskrete Mathematik und Lineare Algebra. 4th edition, Berlin, Heidelberg, Springer Vieweg, 2013
- Nehrlich, Werner: Diskrete Mathematik: Basiswissen für Informatiker. Munich, Vienna, Carl Hanser
Publishing, 2003
- Schwarze, Jochen: Mathematik für Wirtschaftswissenschaftler. Band 1: Grundlagen. 14th edition, Herne, NWB Publishing, 2015
- Teschl, Gerald; Teschl, Susanne: Mathematik für Informatiker. Band 1: Diskrete Mathematik und Lineare Algebra. 4th edition, Berlin, Heidelberg, Springer Vieweg, 2013
Assessment methods and criteria
Portfolio review
Language
German
Number of ECTS credits awarded
6
Semester hours per week
Planned teaching and learning method
Lectures, tutorials (in connection with lecture/seminar), group work
Semester/trimester in which the course/module is offered
1