Apply
now
now
Data & Analytics 2: Mathematics for Computer Science
level of course unit
BachelorLearning outcomes of course unit
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 and co-requisites
none
course contents
- 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 or required reading
- 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 of instruction
Germannumber of ECTS credits allocated
6eLearning quota in percent
20course-hours-per-week (chw)
3planned learning activities and teaching methods
Lectures, tutorials (in connection with lecture/seminar), group work
