Study plan
Compulsory elective modules 1. Semester
Compulsory elective modules 2. Semester
Compulsory elective modules 3. Semester
Compulsory elective modules 4. Semester
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 0SWS
- 5ECTS
- WP
- 0SWS
- 5ECTS
- WP
- 0SWS
- 5ECTS
- WP
- 0SWS
- 5ECTS
- WP
- 0SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
- WP
- 4SWS
- 5ECTS
Compulsory elective modules 5. Semester
Hardware Engineering
Adaptive Systeme
Anerkannte Wahlpflichtprüfungsleistung
Anerkannte Wahlpflichtprüfungsleistung
Anerkannte Wahlpflichtprüfungsleistung
Anerkannte Wahlpflichtprüfungsleistung
Anerkannte Wahlpflichtprüfungsleistung
Angewandte Logiken
Ausgewählte Aspekte der Informatik
BWL-Anwendungen
Componentware
Computergraphik
Controlling
Data Mining in Industrie u.Wirtschaft
Datenethik und Datenschutz
Diagnose- und Therapiesysteme für die Medizin
Digitale Bildverarbeitung
ERP 1 (Standardsoftware)
Effiziente Algorithmen und Datenstrukturen
Entwicklung verteilter Anwendungen
Fortgeschrittene Informationssicherheit
Gestaltung mit elektronischen Medien
IT-Servicemanagement
Informations- und Business Performance Management
Informationssysteme im Gesundheitswesen
Kooperative Systeme
Mobile App Engineering
Modellbasierte Softwareentwicklung
Moderne Datenbanken
Multimedia
Numerische Algorithmen
Rechnerarchitekturen
Robotik
Softwaretechnik C (Softwaremanagement)
Softwaretechnik D (Qualitätssicherung und Wartung)
Systemprogrammierung
Virtualisierung und Cloud Computing
Compulsory elective modules 6. Semester
Module overview
1. Semester of study
BWL- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
45281
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Students recognize the importance of business administration for everyday life and their future professional development as employees or independent entrepreneurs in the IT sector.
Technical and methodological competence:
- The students become aware of the legal and economic consequences of wrong business decisions .
- They learn tools and techniques that enable them to make calculations
- They know the differences between cost centers, cost types and cost units. You will be able to create a cost accounting sheet.You can make cost-conscious decisions and know how a company is structured.
- Students will receive an introduction to project management. They will be able to create a network plan .
- They will be able to link the acquired knowledge of business administration with the available IT programs. (Excel, MS Project)
- Students will work in groups to solve tasks and thus learn the requirements of the team-building process.
Interdisciplinary methodological competence:
Social skills:
Contents
- Historical development of Business Studies
- Legal foundations
- Operation and company, structure, organization and task of company divisions
- Procurement management
- Materials and warehouse management
- Production management
- Sales management
- Business accounting, calculations and cost accounting, BAB
- ABC analysis and project management (network planning technique)
- Company formation, types of company, capital increase
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Group work
- Individual work
- Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
Literature
- Philip Junge: BWL für Ingenieure, Springer Verlag 2012
- Kruse/Heun : Betriebswirtschaftslehr, Winklers Verlag
- Deitermann, M., Schmolke, S., IKR mit Kosten- und Leistungsrechnung, Winklers Verlag
Einführung in die Programmierung- PF
- 10 SWS
- 10 ECTS
- PF
- 10 SWS
- 10 ECTS
Number
41011
Language(s)
de
Duration (semester)
1
Contact time
120 h
Self-study
120 h
Learning outcomes/competences
After completing the course, students will have mastered the most important principles of object-oriented programming on a small scale and have a basic understanding of the structure and functioning of computers.
Technical and methodological competence:
You will acquire the formal competence to understand the principles, methods, concepts and notations of programming on a small scale, to classify them in different contexts and to use them in object-oriented programs. This also includes identifying the algorithmic core of a simple problem and designing an imperative algorithm.
They acquire basic analysis skills that enable them to implement simple object-oriented models in UML notation in the Java programming language. This competence also includes the ability to familiarize themselves independently with applications (such as development environments, learning platforms).
You have the implementation skills to develop and analyze object-oriented programs in Java.
Graduates are familiar with historical developments in computer science. They are aware of the security problems associated with the use of information processing systems. They have key qualifications such as the ability to use new media. They have experience in solving application problems in a team.Social skills:
Students acquire communicative competence in order to present their ideas and proposed solutions convincingly in writing or orally, even if their counterparts are not familiar with the computer science way of speaking and thinking.
Contents
- Fundamental concepts of computer science
- Procedures for the step-by-step development of programs
- Elements of imperative programming: data types, control structures, operations
- Elements of object-oriented programming: objects, classes, interfaces, inheritance, polymorphism
- Description methods of object-oriented programming, e.g. UML
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
- Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
- Participation in project week (ungraded)
Requirements for the awarding of credit points
- passed written exam
- successful participation in project week (2 SWS internship)
- participation in at least 80% of the attendance dates in the project week
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
Literature
- H. Balzert, Java: Der Einstieg in die Programmierung, 4. Auflage, Springer Campus, 2013
- H. Balzert, Java: Objektorientiert programmieren, 3. Auflage, Springer Campus, 2017
- H. P. Gumm, M. Sommer, Grundlagen der Informatik: Programmierung, Algorithmen und Datenstrukturen, Oldenbourg, 2016
- S. Goll, C. Heinisch, Java als erste Programmiersprache, 8. Auflage, Springer Vieweg, 2016
- D. Ratz, J. Scheffler, D. Seese, J. Wiesenberger, Grundkurs Programmieren in Java, 7. Auflage, Hanser, 2014
- C. Ullenboom, Java ist auch eine Insel, 12. Auflage, Galileo Press, 2016 (siehe auch http://openbook.galileocomputing.de/javainsel/)
Projektwoche
Das Modul beinhaltet eine Projektwoche (I9PB-41012, 2 SWS). Die Klausurarbeit und die Projektwoche können unabhänig voneinander abgelegt werden. Für das Bestehen des Moduls ist neben einer Klausur die erfolgreiche Teilnahme an der Projektwoche erforderlich. Die Note des Moduls wird ausschließlich über die Klausurarbeit definiert. Die Projektwoche wird als 5-Tägige Blockveranstaltung im Anschluss an die Vorlesung angeboten.
Mathematik für Informatik 1- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
41064
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- Students master basic mathematical concepts of computer science and their methods such as set theory, relations, propositional logic, complex numbers as well as groups and solids.
- Students who have completed the module have mastered basic and advanced concepts and methods from linear algebra and are able to apply these methods with reference to their practical applications to solve typical tasks in computer science.
- The graduates demonstrate a confident handling of the concepts and methods of vector and matrix calculus and their geometric interpretation, setting up and solving linear systems of equations as well as dealing with straight lines and planes.
Interdisciplinary methodological skills and self-competence:
- Graduates of the module are able to solve computer science problems by setting up and calculating the corresponding mathematical models (for example by setting up and solving linear systems of equations). They demonstrate confidence in the appropriate selection of problem-specific solution methods and their application. The students are able to recognize the mathematical structures they have learned in other areas of computer science and to transfer the methods they have learned to these areas.
- The participants understand the relevance of the content taught to their field of study and are able to communicate this relevance adequately.
Social skills:
Contents
The event includes the following topics:
- Basics of mathematics for computer scientists: Introduction to set theory, cardinality of sets, relations, basics of propositional logic, complex numbers, groups and solids.
- Vectors and vector calculus: notation and interpretation, operations on vectors and their properties (addition, scalar multiplication, scalar product, cross product), vector spaces, length of vectors, collinearity, linear dependence and independence, concepts of dimension and basis, angles between vectors.
- Lines and planes: Representation in linear algebra, applications, positional relationships between points / straight line / planes
- Matrices: Notation and interpretation, operations on matrices and their properties (transposing matrices, addition, scalar multiplication, matrix multiplication), Gaussian algorithm, determinants, inverse matrices and their calculation
- Linear systems of equations: motivation and applications, matrix-vector form of linear systems of equations, Gaussian algorithm for solving linear systems of equations, homogeneous and inhomogeneous linear systems of equations and their relationships, rank of a matrix and relation to the solution set of linear systems of equations
- Eigenvalues and basic transformations
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
Literature
- Skript zur Vorlesung,
- G. Teschl und S. Teschl, Mathematik für Informatiker 1, 3. Auflage, Springer Verlag (2008) - im Intranet der FH elektronisch verfügbar.
- G. Teschl und S. Teschl, Mathematik für Informatiker 2, 2. Auflage, Springer Verlag (2007) - im Intranet der FH elektronisch verfügbar.
- G. Fischer, Lineare Algebra, Vieweg, Braunschweig/Wiesbaden, 12. Auflage (2000).
- Preuß, W., Wenisch, G., Lehr- und Übungsbuch Mathematik für Informatiker.
Rechnerstrukturen und Betriebssysteme 1- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
41031
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Students learn about the basic structure of a computer, from simple digital circuits to a typical microprocessor and computer architectures to basic concepts of an operating system.
Technical and methodological competence
- Computer-oriented representation of information (numbers and characters)
- Describing gates and their function, designing simple switching networks, specifying the function of a switching network as a Boolean expression and as a truth table
- Understanding the structure and use of memory elements (selected latches and flip-flops)
- Sketch the structure and basic understanding of how microprocessors and computer architectures work
- Understanding simple machine programs
- Sketch and evaluate simple implementations of the three central tasks of an operating system (process, memory and file management)
- Practical application of the Linux operating system
Social skills
- Solving programming tasks in groups of two
- Presenting the results to the supervisor
Contents
- Number and character representation (positive and negative integers, fixed and floating point representation IEEE 754, ASCII/Unicode)
- Fundamentals of digital technology (switching algebra, gates, normal forms, optimizations)
- Arithmetic and logic (simple standard switching networks - from multiplexer to ALU)
- Memory (RS latch, reference to automata theory, flip-flops, simple standard switching networks)
- Computer architecture (machine types, von-Neumann and Harvard, approaches to modernization, current processors)
- Microprocessor architecture and programming (case study Atmel AVR ATmega)
- Introduction to the practical application of Linux (files and directories, input/output redirection, processes)
- Operating system concepts (architectures)
- Processes (administration, scheduling)
- Memory management (free memory management, swapping, virtual memory)
- File systems (FAT, Unix inodes)
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Internship accompanying the lecture
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science Dual
Literature
- Tanenbaum, A.S., Rechnerarchitektur: Von der digitalen Logik zum Prarallelrechner, 6. Aufl., Pearson Studium, 2014.
- Hoffmann, D.W., Grundlagen der Technischen Informatik, 5. Aufl., Hanser, 2016.
- Tanenbaum, A.S., Moderne Betriebssysteme, 4. Aufl., Pearson Studium, 2016.
- Stallings, W., Operating Systems: Internals and Design Principles, 9th ed., Prentice Hall, 2017.
Theoretische Informatik- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
42041
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- Be able to name basic terms and properties of formal languages, grammars and the corresponding automata .
- Create grammars and automata for formal languages and understand how they work.
- Be able to convert the representation of languages between grammars, automata and regular expressions. Be able to independently assess problems as formal languages and classify them with regard to the language types in the Chomsky hierarchy.
Interdisciplinary methodological competence:
- Be able to independently assess and classify problems in terms of their complexity .
Contents
- Formal languages and grammars: Alphabet; words: languages; grammars; derivations; grammar types in the Chomsky hierarchy
- Regular languages: programming finite automata (deterministic and non-deterministic); minimization of automata; regular expressions; conversion between grammars, automata and regular expressions; closure properties, pumping lemma for regular languages
- Context-free languages: pushdown automata; Chomsky normal form; word problem with the CYK algorithm; termination properties; pumping lemma for context-free languages
- Turing machines: variants (deterministic and non-deterministic); universal Turing machines; Gödel number; P/NP problem
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Solving practical exercises in individual or team work
- Group work
- Individual work
- Presentation
- Mini-exams during the semester for regular feedback
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Computer Science Dual
Literature
- Hopcroft, J.E., Motwani, R., Ullman, J.D.; Einführung in die Automatentheorie, Formale Sprachen und Berechenbarkeit; Pearson Studium; 3. Auflage; 2011
- Hoffmann, D.W.; Theoretische Informatik; Hanser; 3. Auflage; 2015
- Hedtstück, U.: Einführung in die Theoretische Informatik; Oldenbourg; 5. Auflage; 2012
- Erk, K., Priese, L.; Theoretische Informatik; Springer; 4. Auflage; 2018
2. Semester of study
Mathematik für Informatik 3- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
42073
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Acquisition of basic knowledge of applied statistics and the ability to select and apply descriptive and inductive statistical methods to solve problems of practical relevance.
Technical and methodological competence:
- Acquisition of methodological basics of descriptive and inferential statistics
- Describing essential structures in data by selecting suitable descriptive means
- Converting problems into random variables and suitable distribution assumptions
- Drawing inferences from samples to populations using parameter and interval estimation
- Formulation of test problems and independent implementation of hypothesis tests
- First experience with the computer-aided analysis of data
Interdisciplinary methodological competence:
- Supporting decision-making processes through descriptive data analysis and statistically sound statements
- Transferring estimation and test procedures to problems in computer science
- Applying statistical methods in connection with the evaluation of databases
- Simulation of stochastic processes with the help of theoretical distributions
- Derivation of forecasts with the help of statistical estimation methods
Contents
- Empirical frequency distributions and graphical representations
- Location measures, measures of dispersion and box plots
- Measures of correlation and exploratory regression
- Concept of probability, random events, Laplace model
- Combinatorics
- Conditional probability, independence of events, Bayes' theorem
- Distribution and parameters of discrete random variables
- Equal distribution, binomial distribution, hypergeometric distribution
- Distribution and parameters of continuous random variables
- Equal distribution, normal distribution, central limit theorem
- Point estimators and their properties
- Confidence intervals for expected value and proportion value
- Testing hypotheses, binomial test, Gaussian test, t-test
- Independent computer-aided analysis of data sets, e.g. in Excel. Python or R
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
- Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Business Informatics
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
Literature
- Fahrmeir et al.; Statistik: Der Weg zur Datenanalyse; Springer; Berlin Heidelberg; 8. Auflage; 2016
- Vorlesungsskript
Algorithmen und Datenstrukturen- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
42012
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Students will have mastered selected algorithms and data structures after completing the lecture. They can analyze and qualitatively evaluate algorithms.
Technical and methodological competence:
You will acquire basic analytical skills to be able to evaluate, compare and explain algorithms and data structures and their properties. This competence also includes the ability to familiarize themselves independently with applications (such as APIs and development environments).
You have the implementation skills to transfer data structures and algorithms into object-oriented programs and to use predefined data structures and algorithms in libraries, such as the collections in Java, to solve problems.
You will acquire the formal competence to identify the core of a simple problem and to formulate and use suitable algorithms and data structures to solve it. They recognize the recursive core of a problem and can use a recursive problem-solving strategy. They have the competence to assign selected problems to known problem classes.Contents
- Design, analysis and runtime behavior of algorithms
- Recursion
- Search and sorting methods
- Lists, trees, graphs, hash tables
- Reference to modern class libraries such as Java Collections
- Design methods, e.g. divide&conquer, backtracking
- Algorithmic problem classes
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Internship accompanying the lecture
- Group work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
Literature
- H. Balzert, Lehrbuch Grundlagen der Informatik, Elsevier 2005
- G. Saake, K. Sattler, Algorithmen und Datenstrukturen, dpunkt.verlag 2014
- A. Solymosi, U. Grude, Grundkurs Algorithmen und Datenstrukturen in JAVA, Springer Vieweg 2017
Lern- u. Arbeitstechniken- PF
- 2 SWS
- 2 ECTS
- PF
- 2 SWS
- 2 ECTS
Number
411031
Language(s)
de
Duration (semester)
1
Contact time
30 h
Self-study
45 h
Learning outcomes/competences
Interdisciplinary methodological competence:
- The participants know professional standards and procedures in the field of learning and working techniques (including time and self-management, learning theory, communication and effective collaboration as well as creativity techniques).
- The students can apply these across disciplines .
Self-competence:
- The participants are able to use learning methods, communication and presentation techniques, creativity and problem-solving techniques as well as methods of time and self-management profitably for themselves in their studies and work.
Social skills:
- The participants know techniques for effective collaboration in groups.
- Students know how to present content in groups.
- Students are familiar with creativity and problem-solving techniques for groups.
Contents
The course includes modules on the following topics:
- Learning techniques and learning types
- Working techniques (literature research in the library)
- Time and self-management
- Motivation
- Communication techniques and collaboration
- Creativity and problem-solving techniques
- Burnout
- Basics of scientific work
- Mentoring discussions (include questions about choosing a course of study, organizing studies, individual time and learning planning, dealing with difficult situations and preparing for internships)
Teaching methods
Seminar-style teaching with flipchart, smartboard or projection
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
Homework
Requirements for the awarding of credit points
- Successful homework
- Participation in at least 80% of the attendance dates
- Participation in the mentoring program
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
Literature
- Friedrich Rost; Lern- und Arbeitstechniken für das Studium; Vs Verlag 6. Auflage 2010; ISBN-13: 978-3531172934
Die Studierenden sollen durch die Lehrveranstaltung in die Lage versetzt werden, verschiedene Lern-, Arbeits-, Kommunikations- und Selbstmanagementechniken in ihrem Studium und beruflichen Alltag anzuwenden. Das Erlernen dieser Kompetenzen erfordert durch ihre Natur sowohl eine intensive Zusammenarbeit mit und persönliche Anleitung durch die jeweiligen Dozent/-innen, als auch eine Vielzahl praktischer Arbeiten in der Gruppe unter aktiver Supervision durch die Dozent/-innen. Um diese Ziele zu erreichen, ist eine Mindestanwesenheitspflicht in dieser Lehrveranstaltung erforderlich.
Mathematik für Informatik 2- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
41061
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
- the students have understood the proof principle of complete induction and can apply it.
- the students are familiar with the Cartesian representation of complex numbers and can apply the basic arithmetic operations to complex numbers.
- the students know the concept of functions and can determine and name the properties of functions.
- the students are able to determine the limit behavior of sequences, series and functions.
- the students are able to determine Taylor series and approximate functions with the help of Taylor polynomials.
- can differentiate and integrate functions and use this knowledge in applications (e.g. extreme value calculations, de l'Hospital's rule, area calculations).
- know functions in higher dimensions. They can determine extreme points of these functions and calculate multidimensional integrals.
Contents
- Number ranges, full induction
- Functions: Polynomials, rational functions, exponential and logarithmic functions, trigonometric functions and their inverse functions, and other elementary functions
- Convergence of sequences and series
- Limit values and continuity of functions, calculation of zeros of functions
- Differentiability of functions; one- and multidimensional differential calculus
- Rule of de l'Hospital
- Taylor series expansion, approximation of functions by polynomials
- Local and global extrema of functions in one or more variables
- Integration of continuous functions in one and more variables (antiderivative, partial integration, substitution rule)
Teaching methods
- Lecture in interaction with the students
- lecture-accompanying exercise
- active, self-directed learning through tasks and accompanying materials
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
Duration: 90 minutes.
Requirements for the awarding of credit points
The performances are graded and must be completed with a minimum grade of sufficient (4.0).
The performance is considered at least sufficient if at least 50% of the possible points are achieved in both the basic part and the entire examination.
Applicability of the module (in other degree programs)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
Literature
- Forster, O.: Analysis 1, Wiesbaden, Springer Spektrum, 2023, 13. Auflage.
- Forster, O.: Analysis 2, Wiesbaden, Springer Spektrum, 2025, 12. Auflage.
- Papula, L.: Mathematik für Ingenieure und Naturwissenschaftler Band 1 , Wiesbaden, Springer Vieweg, 2024, 16. Auflage.
- Papula, L.: Mathematik für Ingenieure und Naturwissenschaftler Band 2 , Wiesbaden, Springer Vieweg, 2025, 15. Auflage.
- Teschl, G. & Teschl, S.: Mathematik für Informatiker Band 2, Wiesbaden, Springer Vieweg, 2014, 3. Auflage
Programmierkurs 1- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
42021
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Providing the knowledge required to implement application software from a professional point of view. This includes the realization of graphical user interfaces, the connection of technical concept classes and the persistence of data. Concepts of object-oriented programming are applied in a problem-oriented manner.
Technical and methodological competence:- Implementing flexible systems through the use of polymorphism and interfaces
- Recognizing the advantages of regulated exception handling
- Implementing a flexible graphical user interface using components and layout managers
- Using data streams
- Identifying and solving concurrent programming problems
- Reusing components via the targeted use of an application programming interface (API)
Interdisciplinary methodological competence:
- Application of programming techniques in the implementation of commercial, technical and multimedia applications
Contents
- In-depth study of object-oriented programming in Java (abstract classes, interfaces, polymorphism)
- Professional exception handling via exceptions
- Use of collections for object management
- Access to the file system and organization of files (Java IO)
- Use of data streams
- Serialization of objects
- Programming graphical user interfaces (JavaFX)
- Event handling
- Concurrent programming (threads)
- Java Stream API and lambda expressions
- Architecture of application programs from an implementation perspective
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Business Informatics
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
Literature
- Horstmann, C., Cornell, G.; "Core Java, Volume 1: Fundamentals", Pearson, Boston, 2018
- Horstmann, C., Cornell, G.; "Core Java, Volume 2: Advanced Feature", Prentice Hall, Boston, 2016
- Krüger, G., Hansen, H.; "Java-Programmierung - Das Handbuch zu Java 8", O'Reilly Verlag, Köln, 2014
- Urma, R.-G., Fusco, M., Mycroft, A.; "Java 8 in Action: Lambda, streams, and functional-style programming", Manning, 2015
- Epple, A.; "Java FX 8", dpunkt.verlag, Heidelberg, 2015
- Sharan, K.; "Learn JavaFX8", Apress, Springer Science, New York, 2015
- Sierra, K., Bates, B.; "Head First Java", O'Reilly, 2005
Rechnerstrukturen und Betriebssysteme 2- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
42032
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Students will be able to understand and explain the functioning of the elementary components of an operating system: process and thread management, mechanisms for communication and synchronization. Furthermore, students will be able to evaluate advanced computer structures.
Professional competence:- Implement concurrent applications with processes and threads .
- Differentiate the means of inter-process communication.
- Recognize the potential problems of concurrent programs (e.g. race conditions) and select suitable synchronization mechanisms. Implement system programs with the help of system calls.
- Name advanced aspects of computer structures such as multiprocessor systems and outline their implications for operating system structures using examples.
Social skills:
- Solving programming tasks in groups of two
- Presenting the results to the supervisor
Contents
- Operating system programming (C, JAVA and Java Native Interface (JNI))
- Threads (thread model, comparison to processes, threads in Unix and Windows)
- Communication (pipes, FIFOs, semaphores, shared memory, sockets, RPC)
- Synchronization of processes and threads (mutual exclusion, conditional synchronization, rendezvous with semaphores and monitors)
- Input and output (hardware, interrupt, DMA, driver)
- Multiprocessor systems (hardware, scheduling, synchronization)
- Virtual machines (overview of machine types, JavaVM as a virtual stack machine, instruction set of JavaVM)
- Case study (e.g. Linux/Android, Windows)
Teaching methods
Lecture in interaction with the students, with blackboard writing and projection
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science Dual
Literature
- Tanenbaum, A.S.; Bos, H.; Moderne Betriebssysteme; Pearson Studium; 2016
- Stallings, W.; Operating Systems; Pearson, 2017
- Glatz, R.; Betriebssysteme; dpunkt.verlag, 2015
- Tanenbaum, A.S.; Austin, T.; Rechnerarchitektur; Pearson Studium, 2014
Studium Generale- PF
- 2 SWS
- 2 ECTS
- PF
- 2 SWS
- 2 ECTS
Number
411033
Duration (semester)
1
Technisches Englisch- PF
- 2 SWS
- 2 ECTS
- PF
- 2 SWS
- 2 ECTS
Number
41102
Language(s)
en
Duration (semester)
1
Contact time
30 h
Self-study
45 h
Learning outcomes/competences
- Present technical content correctly and comprehensibly in English .
- Use subject-specific vocabulary from IT and technology with confidence.
- Structure presentations logically and convey technical information in a target group-oriented way.
- Participate actively and constructively in technical discussions in English .
- Perform academic work and presentations in English (e.g. citing and using sources).
Contents
- Basics of technical English:
- Introduction to technical vocabulary .
- Description of technical objects and processes.
- Presentation techniques:
- Structuring presentations (introduction, main part, conclusion) .
- Use of visual aids (diagrams, tables, images).
- Rhetorical devices and presentation phrases.
- Scientific work:
- Correct source references and citation techniques .
- Summary of technical content in a precise form.
- Discussion techniques:
- Asking questions, giving feedback and arguing in discussions .
- Practical application:
- Semester-accompanying presentations on technical IT topics.
Teaching methods
- Seminar-style teaching in English .
- Practical exercises:
- Oral and written exercises to describe technical content .
- Discussions and role plays on current IT topics.
- Presentation workshops: Preparation and delivery of presentations.
- Independent research and academic work.
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
R ("Unit")
Requirements for the awarding of credit points
- Passed presentation (10-15 minutes) on a technical topic during the semester, followed by a Q&A session .
- Prerequisite for admission to the examination: attendance and active participation in at least 9 courses
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
Literature
- A1:
"Fairway. A1. Lehr- und Arbeitsbuch"; Herbert Puchta, Klett Verlag, 2005, ISBN-10: 3125014603 - A2, B1, B2:
Williams, E., Kleinschroth, R., Courtney, B. (2018). "Matters Technik - IT Matters 3rd Edition: B1/B2 - Englisch für IT-Berufe". Cornelsen Verlag. ISBN-13: 978-3-06-451522-2 (E-Book: ISBN 978 – 3 –06-451523 – 9)
3. Semester of study
Datenbanken 1- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
43052
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- Know the definition of a DBS and the schema architecture of a DBMS.
- Know the transaction concept and recovery mechanisms.
- Know and use SQL commands for setting up, storing and querying information (DDL, DML, DRL, DCL).
- Exemplarily carry out the administration of database systems.
- Develop stored functions, procedures and triggers.
Social skills:
- Developing, communicating and presenting relational models and database programs in teams of two .
- Collaboratively creating and evaluating learning posters or review questions on the course content.
Professional field orientation:
- Know the requirements of different job profiles in the database environment (database administrator. Database developer, application developer, data protection officer) .
Contents
- Database and transaction concept
- Relational model and operations
- SQL Data Definition Language and Database Integrity
- SQL Data Manipulation Language
- SQL Data Retrieval Language
- SQL Views
- Roles and rights management
- Stored functions, procedures and triggers
- Backup and recovery
Teaching methods
- seminar-style teaching with flipchart, smartboard or projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
- active, self-directed learning through tasks, sample solutions and accompanying materials
- Exercises or projects based on practical examples
- mini-exams during the semester for regular feedback
- The lecture is offered as a video
- Inverted teaching (inverted classroom)
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written examination paper
- examinations during the semester
Requirements for the awarding of credit points
- passed written examination
- successful internship project (project-related work)
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
Literature
- Beighley, L., SQL von Kopf bis Fuß, O'Reilly, 2008.
- Kemper, A., Wimmer, M.; Übungsbuch Datenbanksysteme, Oldenbourg; 2. aktualisierte Auflage, 2009.
- Saake, G., Sattler, K., Heuer A., Datenbanken - Konzepte udn Sprachen, 6. Auflage, mitp, 2018.
Datenvisualisierung- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
43460
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
After successfully completing the module, students know the specialist terminology of data visualization and can use it correctly to describe data visualization problems and systems. They will know essential data structures and methods of data visualization. They know the architecture of common visualization systems.
You will be able to select and use an appropriate visualization method based on the properties of the data and the visualization goal.
Contents
Lecture
- Introduction, terminology, history of visualization
- Data description
- Human influencing factors
- Visualization process
- Fundamental visualization techniques
- Visualization of scalar data
- Visualization of multivariate data
- Visualization of temporal data
- Visualization of geographical-spatial data
- Graph visualization
- Interaction techniques
Exercise
- Testing of systems for data visualization, e.g. VTK, Tableau
- Solving specific visualization problems
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Solving practical exercises in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
Oral examination
Requirements for the awarding of credit points
passed oral examination
Applicability of the module (in other degree programs)
Bachelor's degree in computer science
Literature
- Schumann, H., Müller W.: Visualisierung, 1. Auflage, Springer Verlag, 2000
- Ward M., Grinstein G., Keim D.: Interactive Data Visualization, 2nd ed., CRC Press, 2015
- Tominski C., Schumann H.: Interactive Visual Data Analysis, CRC Press, 2020
Mathematik für Informatik 4 DS- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
43076
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Expansion of the mathematical skills from the courses Mathematics for Computer Science 1-3, with regard to the mathematical foundations used in the methods of Data Science. Students should be familiar with the specified course content and be able to make informed decisions about which techniques can be used to solve which problems, with the specific issues addressed coming primarily from the areas of fast algorithms, data analysis and compression, image processing and network analysis.
Technical and methodological expertise:
- Acquisition of advanced mathematical methods, especially in the field of statistics and linear algebra
- Understand methods of compression, transformation and projection of data matrices and apply them on the computer
- Know and apply fundamental algorithmic approximation and optimization methods
- Mapping application problems using graphs and naming and implementing solutions
Interdisciplinary methodological skills:
- Present ideas and proposed solutions in writing and orally
- Structure and analyze problems logically
- Develop solutions cooperatively in a team
Contents
- Calculation and properties of eigenvalues and vectors
- Special matrices, norms of vectors and matrices
- Singular value decomposition, principal components, pseudoinverse
- Discrete Fourier, cosine and wavelet transforms, etc.
- Probability distributions, covariance matrices, properties of parameter estimators, maximum likelihood estimators
- Linear and logistic regression (model, parameter estimators, variable selection criteria, )
- Optimization methods (Newton method, Lagrange multiplier, stochastic gradient descent, )
- Graph theory (graphs, trees, networks )
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
- Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
Bachelor's degree in computer science
Literature
- B. Lenze, Basiswissen Lineare Algebra, Springer Vieweg Verlag, Wiesbaden, 2020, zweite Auflage.
- G. Strang, Linear Algebra and Learning from Data, Wellesley-Cambridge Press, Wellesley, USA, 2019
- V. Turau und Ch. Weyer, Algorithmische Graphentheorie, De Gruyter, Berlin, 2015
- M. Aigner, Diskrete Mathematik, Vieweg Springer-Verlag, Berlin-Heidelberg, 2006
Programmierkurs 2 DS- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
43021
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- Use the programming languages Python and R practically for analyses
- implement programs in Python and apply initial data science methods to sample data
- Realize advanced programs for data analysis from data acquisition to analysis and visualization with established libraries
Interdisciplinary methodological competence:
- Solving more complex data analysis problems
- Processing and documentation of results
Social skills:
- Developing solutions in teams
- Presenting the results to the supervisor
Contents
- Introduction to the Python programming language
- Peculiarities of dynamically typed languages
- Control structures
- Fundamental data structures such as lists, tuples, strings and dictionaries
- Structured and object-oriented programming with Python
- Functional programming with Python using Map, Filter, Reduce, List Comprehensions
- Use of libraries such as NumPy, SciPy, Pandas for data analysis
- Tools in the Python environment such as Jupyter Notebooks
- Basics of R: vectorized operations, vectors, lists, matrices, data frames, functions and packages
- Documentation with R Markdown in RStudio
- Application of R using the example of the evaluation of empirical studies
- Basics of visualization in Python and R with Matplotlib and ggplot
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- Oral examination
- Project work with oral examination
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
Bachelor's degree in computer science
Literature
VanderPlas, J., "Python Data Science Handbook", O Reilly, 2017
Ligges, U.; "Programmieren in R", Springer, 2009
Wickham, H. und Grolemund, G., "R für Data Science", Heidelberg, O'Reilly, 2017
Softwaretechnik 1- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
43051
Language(s)
de
Duration (semester)
1
Contact time
120 h
Self-study
30 h
Learning outcomes/competences
Introduction to the implementation of software projects with a special focus on the early phases of development and modeling of software-based solutions with the help of creative methods (e.g. design thinking) and the methods of requirements engineering. Consideration of the integration of AI-based modules in the development process and in the design of the software project, taking into account social implications and regulatory framework conditions.
Modeling of the software system with the Unified Modeling Language (UML) and Domain Driven Design (DDD) methods. Knowledge of various process models and practical experience with agile methods such as Scrum.Technical and methodological competence:
- Overview of procedure and process models of software development
- Name and apply various requirements engineering methods
- Differentiate, specify and formulate user and system requirements
- Verifying and validating requirements
- Overview of the consequences of digitalization and digital transformation with a special focus on the effects in the area of software engineering
- Knowing and applying innovation methods
- Be able to integrate AI-based modules into the development process
- a) Impact on the development process
- b) Consideration of regulatory framework conditions
- c) Analysis of social implications
- Describe the methodological approach in object-oriented analysis
- Know and apply the relevant UML description tools in the context of OOA
- UML use case diagram
- UML package diagram
- UML class diagram
- UML activity diagram
- UML sequence diagram
- UML communication diagram
- UML state diagram
Interdisciplinary methodological competence:
- Modeling the static and dynamic aspects of an OOA model for an object-oriented software system to be developed
- Object-oriented specification of software systems using the Unified Modeling Language (UML)
- Creation of a technical concept or product model for a software system
- Recognizing contradictions, incompleteness, inconsistencies
Social skills:
- Systematically analyze problems of medium complexity in a team
- Develop a requirements specification in a cooperative and collaborative team
- Specify an OOA model for a software system in a cooperative and collaborative team
Contents
- General basics of software engineering (motivation, definitions, goals,...)
- Procedure models (classic to agile)
- Fundamental terms, phases, activities and procedures in the context of requirements engineering
- Digitalization, change and creative methods in the context of software engineering
- Peculiarities of the integration of AI-based modules
- Fundamental terms, methods and notation in the context of object-oriented analysis (OOA) and domain-driven design (DDD)
- Object-oriented analysis with UML (including use cases, packages, activity diagram, class diagram, state diagram, scenario)
- Analysis patterns, static/dynamic concepts and sample applications
- Checklists for the OOA model
- Components and contents of the OOA documentation
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Internship to accompany the lecture
- Project work accompanying the lecture with final presentation
- Workshops
- Group work
- Individual work
- Case studies
- Excursion
- Project work
- The lecture is offered as a video
- Inverted classroom teaching
- Concluding presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- Oral examination
- Project work with oral examination
- Homework
- Presentation
Requirements for the awarding of credit points
- successful project work
- successful term paper
- successful presentation
- successful internship project (project-related work)
- participation in at least 90% of the attendance dates for exercise and internship
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science Dual
Literature
- Balzert, H. (2009): Lehrbuch der Softwaretechnik - Basiskonzepte und Requirements Engineering (3. Aufl.), Heidelberg: Spektrum Akademischer Verlag.
- Ludewig, J.; Lichter, H. (2013): Software Engineering - Grundlagen, Menschen, Prozesse, Techniken, 3. korrigierte Auflage, Heidelberg: dpunkt-Verlag.
- Oestereich, B., Scheithauer, A. (2013): Analyse und Design mit UML 2.5, 11. Auflage, München: Oldenbourg Verlag.
- OMG (2017): UML Specification Version 2.5.1, http://www.omg.org/spec/UML/2.5.1/PDF.
- Pichler, R. (2008): Scrum, Heidelberg: dpunkt-Verlag.
- Pohl, K., Rupp, C. (2015): Basiswissen Requirements Engineering, 4. überarbeitete Auflage, Heidelberg: dpunkt-Verlag.
- Rupp et. al. (2012): UML 2 glasklar. 4. Auflage, Hanser-Verlag.
- Sommerville, I. (2012): Software Engineering, 9. Auflage, München: Pearson Studium.
Begründung zur Teilnahmeverpflichtung
Die Studierenden erarbeiten in Teamarbeit sowohl kreative Lösungen als auch formale Beschreibungen für konkrete Fragestellungen und UseCases aus der Industrie. Dabei werden Sie von den Lehrkräften begleitet und gecoacht. Um die dabei gemachten Erfahrungen zu analysieren und die sich daraus ergebenden Lernziele zu erreichen ist eine Mindestanwesenheitspflicht im Praktikum erforderlich.
Web-Technologien- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
46898
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
This module provides students with an overview of the most important technologies used today to create web applications. After completing the course, they will have mastered the central principles and concepts on which modern web architectures are based.
Technical and methodological competence:
- Completers of the module will be able to name the central basic principles of the WWW and classify them in the context of web applications .
- They acquire the professional competence to differentiate between client-side and server-side web development techniques. They can also name and use important client- and server-side technologies for the creation of web applications. Students recognize basic architectural patterns of web applications and can model them. They can name the inherent technology-independent structural features of web applications and transfer them to specific technologies.
- The participants have mastered the analysis of a comprehensive requirement and can break it down into sub-requirements. They have experience of implementing partial requirements over several weeks as part of an overall project in a team. Students can describe and categorize architectures of software systems.
- The participants develop and implement solutions cooperatively in a team .
- They are also able to explain and discuss their ideas and solutions.
- Students acquire knowledge of typical tasks in web development and the application of specific web technologies. In addition, they gain experience in the use of essential software development tools, such as development environments or build management tools.
Interdisciplinary methodological competence:
Social skills:
Professional field orientation:
Contents
The lecture covers the following topics:
- Detailed knowledge of the structure of websites with HTML and CSS
- Server-side technologies for the development of web applications (e.g. with Java, JavaScript)
- Basic knowledge of web architectures based on the MVC pattern
- Introduction to web services (e.g. REST)
- Client-side technologies for the development of web applications (e.g. JavaScript)
- Fundamental concepts and techniques in the browser (e.g. DOM, AJAX)
- Basic knowledge of responsive web design
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Solving practical exercises in individual or team work
- Internship accompanying the lecture
- Processing programming tasks on the computer in individual or team work
- Group work
- Active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials
- Inverted teaching (inverted classroom)
- E-learning
- Blended learning
- Just-in-time teaching
- Use of learning games
- Screencasts
- Project-oriented internship in teamwork
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Medical Informatics Dual
Literature
- Wolf J.; HTML5 und CSS3: Das umfassende Handbuch; Rheinwerk Computing; 4. Auflage; 2021
- Bühler P., Schlaich P., Sinner D.; HTML5 und CSS3: Semantik - Design- Responsive Layouts; Springer Vieweg; 2017
- Simpson K.; Buchreihe "You Don't Know JS" (6 Bände); O'Reilly; 2015
- Haverbeke M.; JavaScript: richtig gut programmieren lernen; dpunkt.verlag; 2020, 2. Auflage
- Springer S.; Node.js: Das umfassende Handbuch; Rheinwerk Computing; 4. Auflage, 2021
- Tilkov S., Eigenbrodt M., Schreier S., Wolf O.; REST und HTTP; dpunkt.verlag; 3. Auflage; 2015
- Balzert H.; Lehrbuch der Softwaretechnik. Entwurf, Implementierung, Installation und Betrieb. Spektrum Akademischer Verlag; 3. Auflage; 2011
- Tanenbaum A.; Computernetzwerke; Pearson Studium; 3. Auflage; 2000
4. Semester of study
Angewandtes Maschinelles Lernen- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
45470
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
The course deals with the application and analysis of machine learning methods in applications of computer science, medical informatics, business informatics or for general information systems.
Technical and methodological competence:
After attending the course, students will be able to
- use the most important concepts of machine learning to explain learning systems .
- design, implement and analyze machine learning systems for specific applications in computer science
- assess the use of machine learning methods for their own application tasks. To this end, students are familiar with typical applications for these methods. question and discuss the ethical principles of machine learning systems.
- formulate ideas and proposed solutions in writing and orally
- solve tasks independently in the exercises and practicals and present the results
- Develop solutions cooperatively in the exercise and project phases
- plan, distribute and jointly carry out tasks for solutions in the project phases
- argue in a goal-oriented manner in discussions and deal with criticism objectively
- Present the results of group work together
- Evaluate project results and formulate suggestions for improvement
- Recognize and reduce existing misunderstandings between discussion partners
Self-competence:
The student can:
Social skills:
The student can:
Contents
- Basic concepts of machine learning
- Use of Python for machine learning
- Designing evaluation studies for machine learning methods and conducting such studies
- Next neighbor methods and lazy learning
- Linear models
- Different models of supervised and unsupervised neural networks
- Support vector machines
- Decision trees, random forest, gradient boosting machines (GBM)
- Unsupervised learning methods (k-means, SOM)
- Deep learning models (convolutional neural networks (CNN), long short-term memory (LSTM), transformer architectures e.g. BERT)
- Deep learning concepts - transfer learning, data augmentation, generative adversarial networks (GAN)
- Explanability of models
- Applications with data from different modalities (text, image, sound), Word2Vec, FastText, Transformer
- Methods for improving generalization performance (regularization, feature selection, dimension reduction, complexity adjustment)
- Problem solving using the example of course-related mini-projects from industrial applications (student mini-projects in teams of 2-3)
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Internship to accompany the lecture
- Processing programming tasks on the computer in individual or team work
- project work accompanying the lecture with final presentation
- Exercises or projects based on practical examples
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written examination paper or oral examination (according to the current examination schedule)
Requirements for the awarding of credit points
passed written examination or passed oral examination (according to current examination schedule)
Applicability of the module (in other degree programs)
Bachelor's degree in computer science
Literature
- I. Witten, E. Frank, M. Hall und C. J. Pal, Data Mining: Practical Machine Learning Tools and Techniques, 4. Auflage, Morgan Kaufmann (2017) - elektronische Version im Intranet verfügbar
- C. M. Bishop, Pattern Recognition and Machine Learning, Springer (2006)
- E. Alpaydin, Introduction to Machine Learning (Adaptive Computation and Machine Learning), Third Edition, MIT Press (2014)
- I. Goodfellow, Y. Bengio und A. Courville: Deep Learning, MIT Press (2016)
Data Science Datenbanken- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
44270
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological skills:
- Develop EER models and transfer them to relational and non-relational databases. Discuss limitations and alternatives to the relational database model.
- Explain data exchange formats, data migration and information integration using examples. Discuss distributed database architectures for big data applications.Know the methods and limitations of horizontal and vertical scaling.Perform performance optimization using examples.
- Know data mining processes.
- Apply methods of information retrieval and data analysis.
Social skills:
- Developing, creating, communicating and presenting learning content in teams
Contents
Relational databases
- Data modelling (EER model) and normalization
- Data exchange formats, data integration (ELT vs ETL) and data migration using examples
- Memory access structures, performance optimization and SQL tuning
- Limitations of relational databases
Big data and data science
- CAP theorem
- Alternative solution approaches for big data applications
- Architectures of distributed database applications
- Information retrieval and text mining
- Methods of data analysis
Project and current applications
Teaching methods
- seminar-style teaching with flipchart, smartboard or projection
- Solving practical exercises in individual or team work
- Internship to accompany the lecture
- Processing programming tasks on the computer in individual or team work
- Project work accompanying the lecture with final presentation
- Case studies
- Presentation
- active, self-directed learning through internet-based tasks, sample solutions and accompanying materials
- Exercises or projects based on practical examples
- Mini-exams during the semester for regular feedback
- The lecture is offered as a video
- Inverted teaching (inverted classroom)
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written exam paper
- presentation
- examinations during the semester
Requirements for the awarding of credit points
- passed written examination
- successful mini-project (project-related work)
- successful internship project (project-related work)
Applicability of the module (in other degree programs)
Bachelor's degree in computer science
Literature
- A. Bauer, H. Günzel, Data Warehouse Systeme, 2009
- R. Elmasri, S. Navathe, Grundlagen von Datenbanksystemen, 2009
- G. Saake, K.-U. Sattler, A. Heuer, Datenbanken Implementierungstechniken, 2011
- R. Niemiec, Oracle database 12c release 2 performance tuning tips & techniques, 2017
- R. Panther, SQL-Anfragen optimieren, 2014
- S. Edlich, A. Friedland, J. Hampe, B. Brauer, NoSQL Einstieg in die Welt nichtrelationaler Web 2.0 Datenbanken, Hanser Verlag 2010
- M. Kleppmann, Designing data-intensive applications, O'Reilly Media (2017)
- Aktuelle Fachliteratur
IT-Recht- PF
- 2 SWS
- 2 ECTS
- PF
- 2 SWS
- 2 ECTS
Number
45202
Language(s)
de
Duration (semester)
1
Contact time
30 h
Self-study
45 h
Learning outcomes/competences
After attending the course, students will be able to master the legal basics and recognize problems in the context of the design of IT contractual relationships or IT law in general and its specific characteristics, including at EU level. They will learn the special features of the application of the law with regard to IT and will essentially be able to analyze and classify the existing connections between technology and law within the framework of our legal system. They are also able to independently break down the relevant technical issues into the existing legal environment and, on this basis, recognize the legal consequences of their actions and, at the same time, differentiate between those that can be implemented on their own and those that can only be implemented with qualified legal assistance. At the same time, they are also able to assess the consequences of the legal classification for technical development and implementation and to use this knowledge for their further practical work in order to design result-oriented technical processes and developments in a legally resilient manner and to take the path of legally secure IT solutions as part of project management.
Contents
- Contract initiation and conclusion
- Other terminology
- IT law and general terms and conditions
- Other typical problem areas
- The end of contractual relationships
- Choice of law
- Ownership and acquisition of rights
- Copyright
- Warranty and guarantee / typical problem areas
- Liability for breaches of duty and legal violations
- Legal structuring of IT projects
- Data protection
- E-commerce
- Liability/responsibility of the provider
- Legal framework conditions of social networks
- Cloud computing
- Open source software
- Compliance in the company and IT security
- Compliance in the contract
- BYOD
- Advertising, telemarketing and law
- Telephone, telecommunications, unified communications
- IT security law
Teaching methods
Lecture in seminar style, with blackboard writing and projection
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
Literature
- IT- und Computerrecht, Gesetzessammlung, Beck-Texte im dtv;
- Telekommunikations- und Multimediarecht, Beck-Texte im dtv;
jeweils in der aktuellen Ausgabe
Kommunikations- und Rechnernetze- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
46832
Language(s)
en, de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
After completing the course, students will be able to
- Understand the principles, protocols and architecture of the internet
- Use elementary commands of the Linux and Windows operating systems for network configuration and network testing
- Perform and interpret protocol and network analyses with analysis tools
- Analyze existing wired and wireless networks
- Design and implement wired and wireless networks
- Configure network components (router, switch) including VLAN and NAT
Contents
- Reference models (ISO/OSI, TCP/IP)
- Bit transmission layer, transmission media
- Ethernet, network components: Hub, switch, router; virtual LANs (VLAN)
- IP protocols, addressing, routing
- Network Address Translation (NAT)
- Protocols of the transport layer
- IPv6, IPSec, SSL/TLS
- Wireless communication
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Processing programming tasks on the computer in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science Dual
Literature
- Andrew S. Tanenbaum, David J. Wetherall; Computernetzwerke; Pearson Studium; 5. Auflage; 2012
- Douglas E. Comer, Ralph Droms; Computernetzwerke und Internets; Pearson Studium; 3. Auflage; 2001
Künstliche Intelligenz- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
46834
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Fundamental knowledge of concepts and methods of artificial intelligence (AI) and of applications of knowledge-based methods in "intelligent systems". Basic understanding of the possible applications of these methods. Sensitivity for practice-relevant questions.
Technical and methodological competence:
- Capturing and presenting typical AI software architectures .
- Understanding and explaining the paradigms of symbolic and sub-symbolic approaches to AI.
- In-depth explanation and demonstration of heuristic methods of symbolic AI: search, constraints, rule processing. Basic understanding of uncertainty and fuzziness in the context of knowledge-based applications.
- Develop the ability to apply these methods in the context of simple problems. Design and implement small agent programs.
- Understanding and applicability of basic formal logic modeling techniques in the field of AI.
Social skills:
- Development of verbal skills and communication skills in a team by working out solutions in small groups .
Contents
- Basic concepts of artificial intelligence and formal knowledge processing
- Intelligent agents
- State spaces and heuristic search, alpha-beta search, constraint propagation
- Production control systems
- Uncertain knowledge (probabilism), vague knowledge (fuzzy methods)
- Simple neural networks
- Formal logic modeling in the field of artificial intelligence (e.g. predicate logic)
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- immediate feedback and success monitoring
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science Dual
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Business Informatics
- Bachelor of Computer Science Dual
Literature
- Ingo Boersch, Jochen Heinsohn, Rolf Socher; Wissensverarbeitung. Eine Einführung in die Künstliche Intelligenz für Informatiker und Ingenieure ; 2. Auflage; Spektrum Akademischer Verlag; München; 2007.
- Stuart Russel, Peter Norvig: Künstliche Intelligenz. Ein moderner Ansatz ; 3. aktualisierte Auflage; Pearson; München; 2012.
Seminar - Methodik- PF
- 2 SWS
- 2 ECTS
- PF
- 2 SWS
- 2 ECTS
Number
451811
Language(s)
de
Duration (semester)
1
Contact time
30 h
Self-study
45 h
Learning outcomes/competences
The skills acquired depend on the chosen methodological focus of the seminars. After attending the course, students will be able to:
Technical and methodological competence:
- apply the methodological skills corresponding to the focus of the seminar in their studies and work
Interdisciplinary methodological skills:
- apply the methods learned during the course to an interdisciplinary topic and present it to fellow students in an understandable way
Self-competence:
- independently able to structure, develop and create scientific texts and presentations and to present these results
- independently able to research and evaluate technical-scientific content
Social skills:
- Working in groups and interacting within groups
- Presenting and defending content in groups
As an alternative to this seminar, students can take a "Studium Generale" course, which expands their methodological skills
.Contents
The seminars include topics that expand students' interdisciplinary scientific and methodological skills. The topics are offered each semester with new, up-to-date content by all professors and are offered to students in the university's electronic information service (web) (https://fh.do/inf/seminare). Examples of courses are Presentation techniques, introduction to scientific work, planning and conducting data surveys.
Alternatively, a methodologically oriented course can be taken in the "Studium Generale" in the scope of 2 SWS. The list of selectable courses can be found in the university's electronic information service (https://fh.do/inf/generale).
Teaching methods
Seminar
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
Presentation
Requirements for the awarding of credit points
Regular participation in at least 2/3 of the attendance dates
Applicability of the module (in other degree programs)
- Bachelor's degree in Business Informatics
- Bachelor of Computer Science
- Bachelor of Medical Informatics
Literature
Literatur muss vom Studierenden selbst ermittelt werden.
Übergreifend:
- Balzert, H.; Schröder, M. und Schäfer, C.; Wissenschaftliches Arbeiten; W3l; Witten; 2. Aufl.; 2011
Begründung zur Notwendigkeit der Teilnahmepflicht:
Es handelt sich um eine zu Exkursionen, Sprachkursen, Praktika und praktische Übungen vergleichbare Lehrveranstaltung mit in der Regel maximal 20 Teilnehmern. Durch eine regelmäßige Teilnahme werden die Fach- und Methodenkompetenzen der Studierenden in der Einübung des wissenschaftlichen Diskurses in Gruppenarbeit mit anderen Studierenden und im Dialog mit dem Dozenten erarbeitet und gefestigt. Eine Reflektion der Kompetenzen und damit der Lernziele ist selbstständig nicht ausreichend möglich. Nur ein geringer Anteil der Veranstaltung bezieht sich auf die selbstständige Einarbeitung in die fachlichen Inhalte und die Vorbereitung auf den wissenschaftlichen Diskurs, der größere Anteil bezieht sich auf die gemeinschaftliche Erarbeitung und Reflektion der Kompetenzen, sodass eine regelmäßige Teilnahme an mindestens 2/3 der Präsenzterminen für das Erreichen der Lernziele gegeben ist.
Softwaretechnik 2- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
44121
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Introduction to the topic of software architecture. Starting with terms, methods and perspectives, via architecture models in UML (distribution and component diagrams) to various architectural styles from classic to modern.
Students learn how to convert OOA and/or DDD models into an implementation. In addition to business logic and design patterns, a key focus is on the classification and targeted use of tools/frameworks from the areas of communication, persistence and interface design.
Technical and methodological expertise:
- Understanding the concepts of object-oriented design
- Design and documentation of applications with UML
- Understand the principles, patterns and aspects of software architecture
- Defining, documenting and evaluating architectures
- Describing the architecture and design process
- Describing and classifying modern software techniques
Interdisciplinary methodological competence:
- Thinking in systems
- Designing and documenting target systems
- Process-oriented approach
Social skills:
- Working in small teams
- Results-oriented group work
Contents
- General basics of software architecture (concept, motivation, definitions, goals,...)
- Architecture modeling with UML (distribution and component diagram)
- Architecture drivers and overview of different architecture styles
- Architectural principles and views
- Tier architecture, brokers, component-based architecture, SOA, microservice architectures, cloud native architectures, etc.
- Object-oriented design with UML
- Design patterns
- Communication frameworks and tools
- Databases, persistence frameworks and tools
- Frameworks and tools for interface design
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Internship to accompany the lecture
- Project work accompanying the lecture with final presentation
- Workshops
- Group work
- Case studies
- Excursion
- Project work
- The lecture is offered as a video
- Inverted classroom teaching
- Concluding presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- Oral examination
- Project work with oral examination
- Homework
- Presentation
Requirements for the awarding of credit points
- successful project work
- successful term paper
- successful presentation
- successful internship project (project-related work)
- participation in at least 90% of the attendance dates for exercise and internship
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science Dual
Literature
- Bass et al: Software Architecture in Practice, 3. Auflage, Addison Wesley, 2012.
- M. Fowler: Patterns für Enterprise Application-Architekturen, 1. Auflage (Taschenbuch), mitp, 2003.
- Gamma et al.: Entwurfsmuster: Entwurfsmuster als Elemente wiederverwendbarer objektorientierter Software, mitp, 2014.
- C. Richardson: Microservice Patterns. 1. Auflage, Manning Publications, 2018.
- Rupp et al: UML 2 glasklar, 4. Auflage, Hanser-Verlag, 2012.
- G. Starke: Effektive Softwarearchitekturen: Ein praktischer Leitfaden, 9. Auflage, Hanser-Verlag,2020.
- Vogel et al: Software-Architektur: Grundlagen Konzepte Praxis, 2. Auflage, Spektrum, 2009.
- E. Wolff: Microservices: Grundlagen flexibler Softwarearchitekturen, 1. Auflage, dpunkt-Verlag, 2015.
Begründung zur Teilnahmeverpflichtung
Die Studierenden erarbeiten in Teamarbeit sowohl kreative Lösungen als auch formale Beschreibungen für konkrete Fragestellungen und UseCases aus der Industrie. Dabei werden Sie von den Lehrkräften begleitet und gecoacht. Um die dabei gemachten Erfahrungen zu analysieren und die sich daraus ergebenden Lernziele zu erreichen ist eine Mindestanwesenheitspflicht im Praktikum erforderlich.
Studium Generale- PF
- 2 SWS
- 2 ECTS
- PF
- 2 SWS
- 2 ECTS
Number
451815
Duration (semester)
1
5. Semester of study
Data Science Projekt- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
45475
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
145 h
Learning outcomes/competences
Technical and methodological competence:
- Application of theoretical, conceptual and practical knowledge and skills in data science
- Project management and documentation
- In-depth study of a data science topic
Social skills:
- Working in a team (6-12 people)
- Practicing team structures
Professional field orientation:
- Knowledge of team organization
- Knowledge of the specific requirements of data science in a medium-sized project
Contents
On the basis of a sufficiently detailed description of the project objectives (in some cases provided by partner companies of the UAS) with any requirements already specified by the lecturer, individual groups consisting of 2-3 students take on specific tasks, with one group being responsible for project management and the implementation and documentation of project meetings as well as project planning and monitoring. For the project, the overall system to be developed must be modularized by the students accordingly, interfaces defined and, at the end, the interaction of the modules designed and implemented by the individual groups tested and proven through integration tests. For the implementation of the data science parts, the project should be based on established industry standards such as the CRISP-DM model.
In addition to the specified or selected implementation environments, a document management system, a planning tool, a platform for version management and tools for project planning and control are also used as part of the project implementation. The project participants are also obliged to carry out project-oriented time recording.
Teaching methods
- Project work
- Concluding presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
Project work with oral examination
Requirements for the awarding of credit points
Successful project work
Applicability of the module (in other degree programs)
Bachelor's degree in computer science
ERP 2- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
45392
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Theoretical basic knowledge of ERP systems is taught in the course and previously acquired specialist knowledge is deepened using practical examples based on the SAP® ERP system.
The focus is initially on getting to know the structure of an ERP system, the tasks involved in selection, installation and configuration, as well as the various customization options in the ERP system (SAP® ERP®). Following on from this, the special features of maintaining and operating an ERP system are covered.
In-depth and practical implementation is carried out using a specific ERP system (SAP® ERP®). The processing of various case studies provides insights into practical and relevant aspects. In addition, basic knowledge of the ABAP® programming language is developed, taking into account database access and dialog design.
- Differentiating between standard and customized software
- Naming the advantages and disadvantages of standard software
- Differentiate between the various customization and expansion options of standard software and evaluate the respective consequences
- Operating the ERP system as part of process case studies
- Using the development environment of the ERP system
- Designing and implementing functional enhancements to standard software
- Transferring the knowledge acquired and developing your own solutions as part of a mini-project
Social skills:
- Evaluating the importance of communication, conflict and team skills in implementation and customization projects
- Sensitization to the social problems of an ERP implementation
- Increasing cooperation and teamwork skills in the face-to-face exercises and mini-project
Professional field orientation:
- Knowledge of the requirements of different job profiles in the ERP environment (esp. sales, consulting, project management, application development)
Contents
- Technical structure of the SAP® ERP system (work processes of the application server)
- Change options in SAP® ERP (types of customizations, their delimitation and consequences)
- Development Workbench and its tools (ABAP® Editor, Function Builder, Screen Painter)
- Meaning of the WBO (packages, requests, tasks, transport system, )
- ABAP® programming language (program structure, syntax rules, declarative and operative commands)
- Modularization options in ABAP® (subroutines, function modules)
- Objects of the data dictionary (domains, data elements, tables)
- Dialog programming (screens, PAI/PBO modules, input help, )
- Inhouse developments (functional expansion of an ERP system in practical exercises based on a mini-project)
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
- Project work accompanying the lecture with a final presentation
- Group work
- Individual work
- Case studies
- Exercises or projects based on practical examples
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written examination paper
- examinations during the semester
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
Bachelor's degree in Business Informatics
Literature
- Färber, Günther; Kirchner, Anja (2008): ABAP - Grundkurs. 4. Auflage. Galileo Press.
- Keller, Horst; Krüger, Sascha (2006): ABAP Object: ABAP-Programmierung mit SAP NetWeaver. 3. Auflage. Galileo Press.
- Kühnhauser, Karl-Heinz (2005): Einstieg in ABAP. Galileo Press.
Informatik und Gesellschaft- PF
- 2 SWS
- 2 ECTS
- PF
- 2 SWS
- 2 ECTS
Number
45201
Language(s)
de
Duration (semester)
1
Contact time
30 h
Self-study
45 h
Learning outcomes/competences
Expert knowledge
- Students can describe the subject of computer science and its significance for society .
- The students understand that technology design and appropriation are social processes and can relate this understanding to their own projects and current social IT topics.
- Students are familiar with theories and concepts of the socio-technical perspective and can describe their contribution to the success of IT projects. Students can name and describe relevant representatives of computer science and actors in the field of computer science in our society.Students know facts about current, socially significant IT topics and can discuss them critically.
- Students can address their responsibility as computer scientists .
- Students begin to reflect on their own role as computer scientists .
- Students are sensitized to the impact of IT on an individual and societal level .
- Students are aware of the importance of social processes for the success of IT projects .
Self-competence
Social competence
Professional field orientation
Contents
- Current IT topics and projects: Big data, health apps, UN resolution on privacy on the internet, Network Enforcement Act, General Data Protection Regulation, ethical guidelines, digital disruption ...
- Classification of the subject computer science & society
- Socio-technical systems: fundamentals, principles and methods of design
- Related disciplines: sociology of technology, work and organizational psychology
- IT tools for social systems and digital social networks
- Organizations in the IT environment
Teaching methods
- Lecture in seminar style, with blackboard writing and projection
- Project work accompanying the lecture with final presentation
- Group work
- Individual work
- Presentation
- active, self-directed learning through internet-based tasks, sample solutions and accompanying materials
- the lecture is offered as a video
- Inverted classroom teaching
- Concluding presentation
- Concluding presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- Presentation
- Examinations during the semester
Requirements for the awarding of credit points
- successful presentation
- successful participation in discussion forum
Applicability of the module (in other degree programs)
- Bachelor of Computer Science
- Bachelor of Medical Informatics
- Bachelor of Computer Science Dual
Literature
Bücher, Artikel und Statuten
- ACM. 1992. ACM Code of Ethics and Professional Conduct. Available: http://www.acm.org/about-acm/acm-code-of-ethics-and-professional-conduct; CONTENTS [Accessed 2. Mai 2021].
- ACM. 2015. Software Engineering Code of Ethics and Professional Practice [Online]. Available: https://ethics.acm.org/code-of-ethics/software-engineering-code/ [Accessed 2. Mai 2021].
- GI. 2018. Die Ethischen Leitlinien der Gesellschaft fu r Informatik e.V. Deutschland. Available: https://gi.de/fileadmin/GI/Allgemein/PDF/GI_Ethische_Leitlinien_2018.pdf [Accessed 2. Mai 2021].
- BAUMS, A., SCHÖSSLER, M. & SCOTT, B. (eds.) 2015. Kompendium Industrie 4.0: Wie digitale Plattformen die Wirtschaft verändern und wie die Politik gestalten kann, Berlin.
- GLASER, T. 2009. Die Rolle der Informatik im gesellschaftlichen Diskurs. Informatik Spektrum, 32, 223-227.
- KIENLE, A. & KUNAU, G. 2014. Informatik und Gesellschaft - eine sozio-technische Perspektive, München, Oldenbourg.
- LOLL, A. C. 2017. Akteure im Bereich Informatik und Gesellschaft. Informatik Spektrum, 40, 345-350.
- MÜLLER, L.-S. & ANDERSEN, N. 2017. Denkimpuls Digitale Ethik: Warum wir uns mit Digitaler Ethik beschäftigen sollten Ein Denkmuster. Available: http://initiatived21.de/app/uploads/2017/08/01-2_denkimpulse_ag-ethik_digitale-ethik-ein-denkmuster_final.pdf [Accessed 2. Mai 2021].
- RAHWAN, I., BONNEFON, J.-F. & SHARIFF, A. 2017. The Moral Mashine [Online]. Available: http://moralmachine.mit.edu/hl/de [Accessed 2. Mai 2021].
- SOUROUR, B. 2016. The code I m still ashamed of. freeCodeCamp. https://medium.freecodecamp.org/the-code-im-still-ashamed-of-e4c021dff55e [Accessed 2. Mai 2021].
Webseiten
- https://gi.de
- https://netzpolitik.org
- http://humanetech.com
- https://irights.info
Mensch Computer Interaktion- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
43081
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
The course teaches the basics of user interfaces for efficient cooperation and interaction between humans and computers. In this context, both physiological and psychological aspects of human information processing are covered. Furthermore, software ergonomics is introduced as a scientific field that deals with the design of human-machine systems. Furthermore, the effects on concepts and implementations of software systems and user interfaces are examined and discussed.
Technical and methodological competence:- Observation of the basic learning and action processes when using software
- Knowledge of the standard operating elements for WIMP interfaces
- Name the most important standards, laws and guidelines on SW ergonomics
- Fundamental evaluation of the ergonomics of user interfaces based on these regulations
- Mapping the activities in the user-centered design process to case studies
- Basic knowledge of the most important usability engineering tools and their application in case studies
Interdisciplinary methodological competence:
- Knowledge of simplified action process models
Social skills:
- Observation, assessment and evaluation of communication situations
- Working on tasks in alternating small groups (2-4 students each)
Professional field orientation:
- Interdisciplinarity of user experience design
- Application of simple usability engineering tools (e.g. personas) using a case study
Contents
1. basics
- Introduction and motivation
- Definition of software ergonomics
- Perception
- Memory and experience
- Processes of action
- Communication
2. implementation
- Norms and laws
- Guidelines
- Hardware
- Forms of interaction
- Graphical dialog systems
3. user-centered design
- Introduction
- Web usability
- Accessibility
- Tools of usability engineering
4. further contents
In consultation with the students, one to three of the following topics will be covered. The list will be expanded as required
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- Project work with oral examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
- passed written examination
- passed oral examination
- successful project work
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Medical Informatics Dual
Literature
Die im jeweiligen Semester eingesetzte Prüfungsform (z.B. mündliche Prüfung) wird zu Beginn der Veranstaltung bekanntgegeben. Dies gilt ebenfalls für eine möglicherweise genutzte Bonuspunkteregelung.
Projektarbeit- PF
- 0 SWS
- 5 ECTS
- PF
- 0 SWS
- 5 ECTS
Number
46193
Language(s)
de
Duration (semester)
1
Contact time
3 h
Self-study
147 h
Learning outcomes/competences
Through the project work, students learn the following skills, which prepare them for writing their later thesis and qualify them for starting their career:
Technical and methodological competence
- Solving IT-specific problems, if possible in a business context, by creating a software/hardware solution in an engineering manner (i.e. specifying requirements, weighing up and evaluating alternative solutions, modeling systems and ensuring quality) while taking limited resources into account.
Interdisciplinary methodological competence
- Conducting the work as a project (i.e. setting objectives and planning projects, pre- and post-calculation of the time required), as well as
- Production of the written paper using scientific working methods (including literature research, correct citation).
Self-competence
- Assessment of own work results .
Social skills
- Ability to work in a team with developers and (as far as possible) users, especially: to present work results, to lead and moderate meetings and to resolve conflicts.
Professional field orientation
- Working on practically relevant tasks .
For further details see process description PB-PAAA (Annex IV).
Contents
Students have the right to suggest a project topic. The project should preferably be carried out outside the university (further details are regulated by the VA-PAAA-EXT procedural instructions). Group work is desired. The specific knowledge directly required in the projects will be taught in block courses if necessary.
Regular project meetings give students the opportunity to acquire the above-mentioned teamwork skills by practicing them. In particular, quality assurance is trained through the presentation of results from analysis, design and implementation.
Teaching methods
- Project work
- Concluding presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
Project work with oral examination
Requirements for the awarding of credit points
Successful project work
Literature
Muss von den Studierenden selbst in Bezug zum gewählten Thema der Projektarbeit ermittelt werden.
Übergreifend:
-
- Wissenschaftliches Arbeiten - Wissenschaft, Quellen, Artefakte, Organisation, Präsentation - Helmut Balzert, Christian Schäfer, Marion Schröder - W3L, 2. Aufl., 2011
Seminar - Inhalt- PF
- 2 SWS
- 2 ECTS
- PF
- 2 SWS
- 2 ECTS
Number
45182
Language(s)
de
Duration (semester)
1
Contact time
30 h
Self-study
45 h
Learning outcomes/competences
The skills acquired depend on the chosen focus of the seminars. After attending the course, students will be able to:
Technical and methodological skills:
- apply the content-related skills corresponding to the focus of the seminar in their studies and profession
- use scientific methods to prepare a presentation on the main topic. They can research, evaluate, structure, document and present .
- write a scientific term paper
Self-competence:
- independently able to structure, develop and create scientific texts and presentations and to present these results
- independently able to research and evaluate technical-scientific content
Social skills:
- Working in groups and interacting within groups
- Presenting and defending content in groups
Professional field orientation:
- to develop content corresponding to the occupational field
Contents
The seminars include topics that expand students' specialist academic skills. Students prepare a presentation on a selected special topic in business administration, computer science and/or business informatics and present the content. The topics are offered each semester with new, up-to-date content by all professors and lecturers and are offered to students in the university's electronic information service (web) (https://fh.do/inf/seminare). Examples of courses are Modern Supply Chain Management for Information Logistics, Business Simulation and Social Networks. The professional orientation of the seminars is strengthened by the use of lecturers from Business Studies with special qualifications in the subjects.
Teaching methods
Seminar
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
Presentation
Requirements for the awarding of credit points
- successful presentation
- regular participation in at least 2/3 of the attendance dates
Applicability of the module (in other degree programs)
- Bachelor's degree in Business Informatics
- Bachelor of Computer Science
- Bachelor of Medical Informatics
Literature
Literatur muss vom Studierenden selbst ermittelt werden.
Übergreifend:
- Balzert, H.; Schröder, M. und Schäfer, C.; Wissenschaftliches Arbeiten; W3l; Witten; 2. Aufl.; 2011
Begründung zur Notwendigkeit der Teilnahmepflicht:
Es handelt sich um eine zu Exkursionen, Sprachkursen, Praktika und praktische Übungen vergleichbare Lehrveranstaltung mit in der Regel maximal 20 Teilnehmern. Durch eine regelmäßige Teilnahme werden die Fach- und Methodenkompetenzen der Studierenden in der Einübung des wissenschaftlichen Diskurses in Gruppenarbeit mit anderen Studierenden und im Dialog mit dem Dozenten erarbeitet und gefestigt. Eine Reflektion der Kompetenzen und damit der Lernziele ist selbstständig nicht ausreichend möglich. Nur ein geringer Anteil der Veranstaltung bezieht sich auf die selbstständige Einarbeitung in die fachlichen Inhalte und die Vorbereitung auf den wissenschaftlichen Diskurs, der größere Anteil bezieht sich auf die gemeinschaftliche Erarbeitung und Reflektion der Kompetenzen, sodass eine regelmäßige Teilnahme an mindestens 2/3 der Präsenzterminen für das Erreichen der Lernziele gegeben ist.
Hardware Engineering- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46878
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Teaching the basics of hardware-related implementations within technical computer science. Theoretical knowledge, its application and transfer to structure-based (HW) and behavior-based (SW) solutions.
Technical competence:
- The students should be able to explain Mealy- & Moore automata, building blocks of digital technology, VHDL language elements and basic HW technologies.
- They will be able to explain procedures for the transition from logic to switching algebra, differentiate the relationship between design parameters (performance, area, power consumption, costs) and differentiate between switching algebra procedures.
- The students can minimize switching functions, design switching systems, create simple VHDL programs, configure an FPGA device (Xilinx Spartan 3) and implement a VGA driver.
Social skills:
- Work in the practical part (internship in the 2nd half of the semester) in the field of simulation of VHDL programs and FPGA programming in small groups strengthens communication skills and binding coordination between students .
Contents
- Formal basics
- Terms, classes, forms of representation (tabular, graphical, algebraic)
- Normal forms (KNF, DNF)
- Minimization (Quine/McCluskey, KV, Nelson, Petrick)
- Switching networks
- Sequential logic
- Switching mechanisms & automata
- Components of digital technology, etc.
- Gates
- Flip-flops
- Multiplexers
- Registers
- Adder
- Counter
- Syntax & semantics of the hardware description language VHDL
- Simulation of hardware descriptions
- Design of digital circuits, design of state machines .
- Hardware design in FPGA technology
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Computer Science
- Bachelor of Computer Science
Literature
- Sikora, A, Drechsler, R. Software-Engineering und Hardware-Design, Eine
systematische Einführung, Hanser, 2002 - Becker, B, Drechsler, R., Molitor, P. Technische Informatik, Eine Einführung,
Pearson Studium, 2005. - Reichardt, J., Schwarz, B., VHDL-Synthese, Entwurf digitaler Schaltungen und
Systeme, 3. Auflage, Oldenbourg, 2003. - Molitor, P, Ritter, J., VHDL, Eine Einführung, Pearson Studium, 2004.
Adaptive Systeme- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46901
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
In this course, complex and adaptive systems for problem solving are discussed and implemented. Students acquire various skills in the process.
Technical and methodological competence:
After the students have attended the course
- are able to develop and analyze problem solutions with adaptive systems .
- use the most important concepts of adaptive and adaptable information systems to explain systems. use methods of Computational Intelligence for the design of adaptive systems.
- implement adaptive systems on the basis of the models explained. to evaluate the systems created, where possible.
- recognize the limits of adaptive systems.
The student is able to recognize that methods of adaptive systems can be used to describe properties of technical but also business and social systems and to analyze their behavior.
Social skills:
Cooperation and teamwork skills are trained during the practical phases. Students develop practical implementations in teams of size 2 and 3 and are able to present the developed solution together.
Contents
- Basics and examples of adaptive and complex systems and their application to control systems, networks and the web
- Modeling of adaptation processes using various adaptive techniques
- Application of soft computing methods (including evolutionary algorithms, particle swarm optimization, ant colony optimization, fuzzy logic, neural networks and modern machine learning methods) for system adaptation to (context) changes
- Personalization and modelling of user profiles and context
- Application of data classification methods in decision support systems (including rating systems, collaborative and social recommendation systems)
- Model-based self-adaptive systems
- Time series prediction
- Current applications of adaptive systems in the context of computer science and medical informatics
Teaching methods
- Lecture in seminar style, with blackboard and projection
- Exercise accompanying the lecture
- Internship accompanying the lecture
- Processing programming tasks on the computer in individual or team work
- project work accompanying the lecture with final presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written examination paper or oral examination (according to current examination schedule)
- semester-accompanying coursework (bonus points)
Requirements for the awarding of credit points
passed written examination or passed oral examination (according to current examination schedule)
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science
Literature
- J. Schmidt, Chr. Klüver, J. Klüver, Programmierung naturanaloger Verfahren, Vieweg+Teubner Verlag (2010)
- R. Kruse, C. Borgelt, F. Klawonn, C. Moewes, G. Ruß, M. Steinbrecher, Computational Intelligence, Zweite Auflage, Vieweg+Teubner Verlag (2015)
- W.-M. Lippe, Soft-Computing, Springer Verlag (2005)
- A. Kordon, Applying Computational Intelligence, Springer Verlag (2010)
- I. Witten, E. Frank und M. Hall, Data Mining: Practical Machine Learning Tools and Techniques, 4. Auflage, Morgan Kaufmann (2017), elektronische Version im Intranet verfügbar
Anerkannte Wahlpflichtprüfungsleistung- WP
- 0 SWS
- 5 ECTS
- WP
- 0 SWS
- 5 ECTS
Number
46991
Duration (semester)
1
Anerkannte Wahlpflichtprüfungsleistung- WP
- 0 SWS
- 5 ECTS
- WP
- 0 SWS
- 5 ECTS
Number
46992
Duration (semester)
1
Anerkannte Wahlpflichtprüfungsleistung- WP
- 0 SWS
- 5 ECTS
- WP
- 0 SWS
- 5 ECTS
Number
46993
Duration (semester)
1
Anerkannte Wahlpflichtprüfungsleistung- WP
- 0 SWS
- 5 ECTS
- WP
- 0 SWS
- 5 ECTS
Number
46994
Duration (semester)
1
Anerkannte Wahlpflichtprüfungsleistung- WP
- 0 SWS
- 5 ECTS
- WP
- 0 SWS
- 5 ECTS
Number
46999
Duration (semester)
1
Angewandte Logiken- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46817
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- Completers of the module have mastered advanced formal logic concepts in computer science and are able to transfer concrete classical and non-classical logics, logic concepts and methodologies to various computer science problems, adapt them to the respective needs and finally apply them in practice.
- In particular, students will master the basics of formal logic modeling of dynamic processes and their applicability as well as techniques of formal specification and verification of models. The students can apply these skills across disciplines.
- The participants are able to independently deal with current research papers on formal logic modeling and verification in computer science and to understand the core statements.
- The participants are able to present formal-logical topics and questions in a didactic manner in presentations and written papers. In particular, they are able to present complex formal-logical issues at different levels of granularity (from conveying the pure underlying idea to formulating the exact mathematical facts). The participants are able to lead discussions on scientific issues (in particular with regard to the applicability of the content taught to their respective field of study).The participants understand the relevance of the content taught for their field of study and are able to communicate this relevance adequately.
Self-competence:
Social skills:
Contents
The event includes the following topics:
- Classical concepts of modal logic (such as possibility and necessity) and their relevance in computer science
- Syntax and semantics of classical modal and temporal logics (such as CTL*, CTL and LTL) and their applications
- Formal-logical specification and modeling of computer science processes using possible-world semantics
- (Automated) verification of modeled processes using model checking methods and their applications in practice
- Syntax and semantics of epistemic logics (such as belief sets and epistemic modal logic) and their relevance for computer science
- Exemplary application of the topics learned: depending on the interests and professional background, various example applications can be chosen such as Formal Hardware Verification , Modeling Dynamic Processes , Concurrency , etc.
- Sensible intensional / propositional logics and their applications in modern computer science applications
- Relevance of logics in the applications of artificial intelligence
Teaching methods
- Lecture in seminar style, with blackboard and projection
- Exercise to accompany the lecture
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- oral examination
- presentation
Requirements for the awarding of credit points
- passed oral examination
- successful presentation
Applicability of the module (in other degree programs)
- Bachelor's degree in Business Informatics
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor of Medical Informatics
- Bachelor of Computer Science Dual
- Bachelor of Medical Informatics Dual
Literature
- Hughes und Cresswell A New Introduction To Modal Logic, Routledge Chapman & Hall,
- Kropf Introduction to Formal Hardware Verification, Springer-Verlag Berlin and Heidelberg, 1999
- Chagrov und Zakharyaschev Modal Logic, Oxford University Press, 1997
- Gardenfors - Knowledge in Flux: Modeling the Dynamics of Epistemic States (Studies in Logic), College Publications, 2008
- Bab - Epsilon_mu-Logik - Eine Theorie propositionaler Logiken, Shaker Verlag Aachen, 2007
Ausgewählte Aspekte der Informatik - WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46904
Duration (semester)
1
BWL-Anwendungen- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46990
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- Knowledge of different business administration applications and their possible uses in companies .
- Operate the SAP® ERP system from an application perspective in the context of process case studies.
- Differentiate between the various customization and extension options of standard software and evaluate the respective consequences. Designing and implementing functional enhancements in SAP® ERP.
- Adapting the SAP® ERP system as part of customizing case studies. Using the development environment of the SAP® ERP system.
- Basic knowledge of the ABAP® programming language, taking into account database access and dialog design. Basic knowledge of the development and design of applications using SAPUI5 and SAP Fiori®.
- Evaluate the importance of communication, conflict and teamwork skills in implementation and adaptation projects .
- Sensitize to the social issues of an ERP implementation. Increase cooperation and teamwork skills in the face-to-face exercises and in the mini-project.
- Knowing the importance of different business administration applications for the business processes of companies .
- Knowing the importance of an ERP system in a company's IT.
- Know how to identify and use interfaces between an ERP system and other business applications. Know the requirements of different job profiles in the ERP environment (esp. sales, consulting, project management, application development).
Social skills:
Professional field orientation:
Contents
- Overview of business applications and integrated overall systems (data, process and function integration)
- Basics of SAP® ERP as an integrated overall system
- Standard software and customizing in general and implementation in SAP®
- Introduction to the customization of SAP® ERP systems
- Introduction to programming with ABAP®
- Database access and dialog programming with ABAP®
- Introduction to SAPUI5 and SAP Fiori®
- More complex in-house development as part of a mini-project
- Discussion of other related systems and technologies: Data Warehouse, Big Data, Blockchain ...
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Internship to accompany the lecture
- Processing programming tasks on the computer in individual or team work
- Project work accompanying the lecture with final presentation
- Case studies
- Exercises or projects based on practical examples
- Immediate feedback and performance review in each case
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- Project work with oral examination
- Semester-accompanying study achievements (bonus points)
Requirements for the awarding of credit points
- passed oral examination
- successful project work
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
Literature
Bücher
- Balderjahn, Ingo; Specht, Günter (2016): Einführung in die Betriebswirtschaftslehre. Stuttgart: Schäffer-Poeschel.
- DRUMM, C., KNIGGE, M., SCHEUERMANN, B. & WEIDNER, S. 2019. Einstieg in SAP® ERP - Geschäftsprozesse, Komponenten, Zusammenhänge - Erklärt am Beispielunternehmen Global Bike, Bonn, Rheinwerk Verlag GmbH.
- HANSEN, H. R., MENDLING, J. & NEUMANN, G. 2019. Wirtschaftsinformatik, Berlin, Boston, Walter de Gruyter GmbH. Ergänzende Unterlagen:
https://lehrbuch-wirtschaftsinformatik.org/12/home ; Zugriff geprüft am 2. Mai 2021 - KÜHNHAUSER, K.-H. & FRANZ, T. 2019. Einstieg in ABAP, Bonn, Rheinwerk Verlag GmbH.
- KÜHNHAUSER, K.-H. & FRANZ, T. 2015. Einstieg in ABAP, Bonn, Rheinwerk Verlag GmbH. Online verfügbar: http://openbook.rheinwerk-verlag.de/einstieg_in_abap/ ; Zugriff geprüft am 2. Mai 2021
- LAUDON, K. C., LAUDON, J. P. & SCHODER, D. 2016. Wirtschaftsinformatik - Eine Einführung, Halbergmoos, Pearson Deutschland GmbH.
- LEIMEISTER, J. M. 2015. Einführung in die Wirtschaftsinformatik, Berlin Heidelberg, Springer Gabler
Componentware- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46808
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Introduction to component-based software development and application of what has been learned in practical examples based on EJB.
Technical and methodological competence:
- Knowing and defining the concept of components
- Understanding the challenges of distributed systems
- Knowing solution approaches with and without middleware
- Know typical problems in enterprise applications (transaction protection, security, access control, internationalization, scalability, availability, ...)
- Modeling distributed systems with UML
- Understanding the difference between specification and its realization
- Understanding the EJB specification
- Applying EJB knowledge with the glassfish application server
- Develop an independent solution as part of a project
Interdisciplinary methodological competence:
- Developing a project from any application domain
Social skills:
- Systematically work on problems of medium to high complexity in a team
- Develop an EJB solution in a cooperative and collaborative team
- Document an EJB solution in a cooperative and collaborative team
Contents
- General basics of component technology (motivation, definitions, goals,...)
- Fundamental terms and challenges of enterprise applications (transaction protection, security, access control, internationalization, scalability, availability, ...)
- Software architecture principles and concepts for defining software components and platforms
- Concept of the application server
- Stateless session beans
- Stateful session beans
- Singleton session beans
- Message Driven Beans
- Timer Services
- Entity Manager and Persistent Entities
- Transaction management
- Characteristic features of component-based systems
Teaching methods
- Lecture in seminar style, with blackboard and projection
- Exercise to accompany the lecture
- Solving practical exercises in individual or team work
- Internship accompanying the lecture
- project work accompanying the lecture with final presentation
- Exercises or projects based on practical examples
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- Project work with oral examination
- Presentation
- Semester-accompanying study achievements (bonus points)
Requirements for the awarding of credit points
- passed oral examination
- successful project work
- successful presentation
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- Oliver Ihns et. al.: EJB 3.1 professionell. Grundlagen- und Expertenwissen zu Enterprise JavaBeans 3.1 inkl. JPA 2.0, dpunkt.verlag GmbH, Auflage: 2., 2011
- Jan Leßner, Werner Eberling: Enterprise JavaBeans 3.1: Das EJB-Praxisbuch für Ein- und Umsteiger, Carl Hanser Verlag GmbH & CO. KG; Auflage: 2, 2011
- Clemens Szyperski, Dominik Gruntz and Stephan Murer: Component software. Beyond object-oriented computing, Pearson, 2nd Edition, 2002
- CBSE-Proceedings: nth International Symposium on Component-Based Software Engineering
Computergraphik- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46809
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
After successfully completing the module, students know the terminology of computer graphics and can use it correctly to describe graphics systems. They will know important mathematical concepts, algorithms and data structures of computer graphics and their use in common computer graphics systems.
You will be able to select suitable solutions for problems in the field of computer graphics and develop your own computer graphics applications using a standard programming interface (e.g. OpenGL).
Contents
Lecture
- Introduction:
Visual information processing and its applications, hardware and software of graphical systems - 2D graphics:
2D basic elements and basic algorithms, curves, transformations and clipping, raster conversion - 3D graphics:
3D basic elements, curves and surfaces, body modeling, scene graph and transformations, projection, visibility and occlusion, shader programming, lighting and shading, textures, ray tracing
Internship
- Graphics programming with OpenGL
Teaching methods
- Lecture in seminar style, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Computer Science Dual
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- Nischwitz, A., Fischer M., Haberäcker P., Socher G.: Computergrafik : Band I des Standardwerks Computergrafik und Bildverarbeitung; Springer Vieweg; 4. Auflage; 2019
- Marschner, S., Shirley, P.: Fundamentals of Computer Graphics, 4th. ed., CRC Press, 2016
- Hughes J.F., van Dam A., McGuire M., Sklar D.F., Foley J., Feiner S.K., Akeley K.: Computer Graphics principles and practice, 3rd ed., Addison-Wesley, 2013
- Kessenich, J.; Sellers, G.; Shreiner,D.: OpenGL Programming Guide, 9th ed., Addison-Wesley, 2017
Controlling- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46811
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Students learn the difference between strategic and operational controlling and can assess the importance of strategic corporate planning as the basis for strategic controlling.
Technical and methodological competence:Students learn about and apply operational controlling tools and techniques for annual profit generation. They will be able to determine sales, profit and capital return on investment. They can calculate the contribution margin and make decisions about price elasticity.
You will learn about and apply methods for strategic controlling to maintain the company. SWOT analysis, success factors and success objects, strategic business area analysis and strategic business units will be understood and categorized.Interdisciplinary methodological competence:
Students learn about the use of ERP systems in controlling. They will be able to classify controlling in the structure of business software.Social skills:
Group work strengthens social skills in team building and teaches consideration for others in discussions.
Contents
- Classification of controlling in the company
- The controller as a person
- The controlling control loop
- Revolving planning and the SWOT analysis
- Strategic business units and strategic business areas
- Success objectives and success factors
- Controlling key figures, ROI, balanced scorecard
- Break-even analysis, contribution margin accounting
- Price elasticity
Teaching methods
Lecture in interaction with the students, with blackboard writing and projection
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- Ziegenbein, Klaus, Controlling, Kiehl Friedrich Verlag
- Däumler, Klaus-Dieter, Grabe, Jürgen, Kostenrechnung 2, Deckungsbeitragsrechnung, nwb-Verlag
- Reichmann, Thomas, Controlling mit Kennzahlen, Vahlen Verlag
Data Mining in Industrie u.Wirtschaft- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46843
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Students master important methods and algorithms of modern data analysis for recognizing patterns and structures in large data sets. In particular, they are familiar with the three phases of pre-processing, analysis and evaluation of the data mining process. They will be able to select and apply suitable data analysis methods for specific applications in industry and Business Studies and use them to support decision-making.
Technical and methodological competence:
- Students have a sound knowledge of the data analysis methods covered. The students know which method is suitable for which questions and data types and can classify and interpret analysis results.Students can carry out independent analyses of data sets using both Excel and special software (e.g. R, JMP, ...).
Social skills:
- The students can analyze data sets from practice in teamwork using the methods of the course and present the results to the plenum.
Contents
- Phases of data mining
- Data, relations and data preprocessing
- Multiple regression
- Cluster analysis
- Classification methods
- Association analysis
- Outlier detection
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
- Exercises or projects based on practical examples
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- Project work with oral examination
- Examinations during the semester
Requirements for the awarding of credit points
- passed oral examination
- successful project work
- successful mini-project (project-related work)
Applicability of the module (in other degree programs)
- Bachelor of Medical Informatics
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Business Informatics
- Bachelor of Computer Science
Literature
- Cleve, J., Lämmel, U. (2020), Data Mining, 3. Auflage, De Gruyter, Berlin/Boston
- Runkler, A. (2015) Data Mining: Modelle und Algorithmen intelligenter Datenanalyse, 2. Auflage, Springer VS, Wiesbaden.
- Hastie, T., Tibshirani, R., Friedmann, J. (2009), The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2. Auflage, Springer, New York
Datenethik und Datenschutz- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46818
Duration (semester)
1
Diagnose- und Therapiesysteme für die Medizin- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
43451
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
After completing the module, students will be able to
- explain and outline the basic physical and mathematical processes of medical signaling and imaging
- describe and classify the technical operating principles of common medical devices
- name the most important diagnostic and therapeutic systems, demonstrate their possibilities and limitations and differentiate and independently evaluate their interaction
- recognize and classify biosignals and medical images
- describe and classify clinical workflows
- describe and classify the change in radiology and medical technology from digitalization to artificial intelligence
Social skills:
- Working on and solving tasks in smaller teams, such as the mutual derivation of biosignals or targeted experimentation with an ultrasound device
Professional field orientation:
- Knowing and classifying internationally standardized diagnostic and therapeutic systems typical of the profession and their clinical processes
- Processing and solving mathematical-technical problems with the standard software Matlab®, which is widely used in industry
Contents
- Introduction and motivation: outline of the historical development of medicine and medical technology
- Introduction to the most important medical diagnostic and therapeutic systems, their interaction and differentiation, as well as their clinical workflows: endoscopy, sonography, radiography, fluoroscopy, computer tomography, magnetic resonance tomography, nuclear imaging, interventional radiology, radiotherapy, image-guided surgery
- Basics of digital signal processing (practical course): Introduction to the Matlab® system for solving mathematical-technical problems
- Physics, technology and applications of the most important biosignals: electrocardiography (ECG), electroencephalography (EEG), electromyography (EMG) and electrooculography (EOG)
- Physics, technology and applications of the most important imaging techniques: Microscopy/endoscopy, X-ray imaging, computed tomography, ultrasound, magnetic resonance tomography
- Mathematical methods of medical 3D imaging: image reconstruction
- Introduction to methods of machine learning and artificial intelligence (MLP, neural convolutional networks) and their applications in radiology and medical technology
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Processing programming tasks on the computer in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
Literature
- Dössel, O.; Bildgebende Verfahren in der Medizin; Springer; 2. Auflage; 2016
- Prokop, M.; Spiral and Multislice Computed Tomography of the Body; Thieme; 2. Auflage; 2013
- Bushberg, J.; The Essential Physics of Medical Imaging ; Lippincott Williams & Wilkins; 3. Auflage; 2011
- Handels, H.; Medizinische Bildverarbeitung; 1. Auflage; 2009
- Epstein, C.; Introduction to the Mathematics of Medical Imaging; Prentice Hall; 1. Auflage; 2003.
- Morneburg, H.; Bildgebende Systeme für die medizinische Diagnostik; 3. Auflage; Siemens, 1995
Online textbook:
- Sprawls, P.; The Physical Principles of Medical Imaging, 2nd Ed.: http://www.sprawls.org/ppmi2/
Digitale Bildverarbeitung- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46814
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
The course deals with the development and analysis of systems that use digital image processing methods.
Technical and methodological competence:
After attending the course, students will be able to
- list and explain the stages of digital image processing
- recall and apply important mathematical and algorithmic concepts of digital image processing
- solve image processing problems by combining the methods covered
- develop simple image processing applications using the Matlab® programming system or the Java and ImageJ programming languages
- know examples for the industrial application of digital image processing
Contents
- Introduction to the Matlab® programming language and environment
- Overview of image processing hardware and software
- Image acquisition and discretization
- Procedures for image restoration, image enhancement and geometric manipulation of images
- Morphological image processing and the processing of color images
- Discrete Fourier transform (1D and 2D) and applications
- Methods for image segmentation, feature extraction and image analysis
- Pattern recognition and image classification
- Modern image features - interest points (SIFT)
- Deep learning methods for image classification
Teaching methods
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written examination paper or oral examination (according to the current examination schedule)
Requirements for the awarding of credit points
passed written examination or passed oral examination (according to current examination schedule)
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor of Computer Science Dual
- Bachelor of Computer Science
Literature
- H. Bässmann, J. Kreyss: Bildverarbeitung AdOculos, Springer-Verlag, 2004
- W. Burger, M. J. Burge: Digital Image Processing, Dritte Auflage, Springer-Verlag, 2015, elektronische Version im Intranet verfügbar
- A. Nischwitz, M. Fischer, P. Haberäcker: Computergrafik und Bildverarbeitung, Vieweg+Teubner Verlag, 2007
- R. C. Gonzalez, S. L. Eddins, R. E. Woods, Digital Image Processing, Vierte Auflage, Pearson, 2018
- R. C. Gonzalez, S. L. Eddins, R. E. Woods, Digital Image Processing Using MATLAB, Prentice Hall, 2004
ERP 1 (Standardsoftware)- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46828
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Providing basic knowledge about the importance and development of standard software and raising awareness of the associated problem areas. Theoretical knowledge about types of adaptations to standard software and their practical implementation on a specific ERP system. Consolidation and practical application of previously acquired specialist knowledge using practical examples.
Technical and methodological competence:- Distinguishing between standard and customized software .
- Naming the advantages and disadvantages of standard software.
- Differentiate between the various customization options of standard software and evaluate the respective consequences. Assess the quality and complexity of business processes with regard to correctness,
- Designing and implementing functional enhancements to standard software.
- Evaluate the importance of communication, conflict and team skills in implementation and customization projects. Sensitization to the social problems of an ERP implementation.
- Knowledge of the requirements of different job profiles in the ERP environment (esp. sales, consulting, project management, application development)
efficiency and completeness in integrated systems.
Social skills:
Professional field orientation:
Contents
- General principles (definition of terms, historical development, )
- Standardization concept (classification and differentiation from in-house development, degree of coverage, )
- Integration aspects (technical and organizational integration, examples and consequences, )
- Business management components (financial accounting, HR, logistics, production, )
- Selection process (market overview and breakdown, selection criteria, decision-making process, )
- Implementation of an ERP system (project approach, implementation strategies, procedures)
- Technical basics (system structure, hardware platforms and supported databases, )
- Installation, maintenance and operation of an ERP solution
- Customizations to standard software (types of customizations, their delimitation and consequences, )
- Integrated development environments and programming languages
- Inhouse developments (functional expansion of an ERP system in practical exercises based on a mini-project)
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
- Bachelor of Computer Science Dual
- Bachelor of Computer Science
Literature
- Skript zur Vorlesung (Hesseler, M.)
- Hesseler, M.; Görtz, M.; Basiswissen ERP-Systeme ; w3l-Verlag; Bochum; 2007;
- Ergänzende Literaturempfehlungen (nicht zwingend erforderlich):
- Allweyer, T.; Geschäftsprozessmanagement ; w3l-Verlag; Bochum; 2005;
- Hesseler, M. und Rösel, C.; ERP-Übungsbuch: Entwicklung einer einfachen Fuhrpakrverwaltung in Microsoft Dynamics NAV ; Books on Demand; Norderstedt; 2010;
- Hesseler, M. und Görtz, M.; ERP-Systeme im Einsatz ; w3l-Verlag; Herdecke; 2009;
- Luszczak, A.; "Microsoft Dynamics NAV 2009 - Grundlagen", Microsoft Press Deutschland; Auflage: 1, Unterschleißheim, 2009
Effiziente Algorithmen und Datenstrukturen- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46889
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- Be able to describe basic algorithmic methods .
- Be able to assess problems in terms of their modeling possibilities and algorithmic complexity.
- Be able to describe and implement efficient algorithms and data structures for selected basic problems. Categorize algorithms with regard to their quality under different efficiency aspects.Know concepts and methods for solving combinatorial optimization problems and be able to apply them to a problem.Be able to check the correctness and efficiency of algorithms.
Contents
- Basics
- O-notation
- Graphs
- Graph algorithms
- Shortest paths
- Minimal spanning trees
- Flows in networks
- Matchings
- Tours
- Algorithmic techniques
- Divide and Conquer
- Dynamic programming
- Greedy algorithms
- Optimization problems
- Backtracking
- Branch-and-bound
- Approximation algorithms
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Solving practical exercises in individual or team work
- Group work
- Individual work
- Presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science
Literature
- T. Cormen, C. Leiserson, R. Rivest, C. Stein: "Algorithmen - Eine Einführung", Oldenbourg, 4. Auflage, 2013
- T. Ottmann, P. Widmayer: "Algorithmen und "Datenstrukturen", Spektrum Akademischer Verlag, 6. Auflage, 2017
- G. Pomberger, H. Dobler: "Algorithmen und Datenstrukturen", Pearson Studium, 2008
- R. Sedgewick, K. Wayne: "Algorithmen", Pearson Studium, 2014
- R. Wanka: "Approximationsalgorithmen - Eine Einführung", Teubner, 2006
- B. Vöcking, H. Alt, M. Dietzfelbinger, R. Reischuk, C. Scheideler, H. Vollmer, D. Wagner: "Taschenbuch der Algorithmen", Springer, 2008
Entwicklung verteilter Anwendungen- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46890
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Transfer of knowledge for the development of distributed applications
Technical and methodological competence:
- Understanding the special requirements and challenges of developing distributed systems
- Learning about the principles, architectures and mechanisms of distributed systems
- Knowing the approaches to developing distributed systems
- Converting current concepts into Java programs
Social skills:
- Working in small teams
- Results-oriented group work
Contents
- Scenarios of distributed systems
- Basics of distributed systems
- Distributed data management
- Communication in distributed systems
(request/reply, peer-to-peer, push) - Challenges of distributed systems
(heterogeneity, interoperability, configuration,...) - Quality of distributed systems
(transparency, security, reliability,...) - Architectures
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Processing programming tasks on the computer in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Computer Science Dual
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
Literaturhinweise
- Bengel, Günther: Grundkurs Verteilte Systeme, 4. Auflage Springer Vieweg, 2014
- Dustar, Schahram et. al.: Softwarearchitekturen für verteilte Systeme, Springer, 2003
- Hohpe, Gregor, Woolf, Bobby: Enterprise Integration Patterns, Addison Wesley, 2004
- Kopp, Markus, Wilhelms, Gerhard: Java Solutions
Fortgeschrittene Informationssicherheit- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46900
Language(s)
en
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
The students are able to apply methods,
best practices and
- apply methods, best practices and software tools relevant in practice for the development of secure software.
- independently evaluate various cryptographic methods as part of a software development project and select adequate cryptographic methods on this basis.
- independently develop software that uses cryptographic methods and systematically test the software.
Contents
- Java Cryptography Architecture and API
- Legion of the Bouncy Castle Java Cryptography APIs
- Block ciphers: AES, padding, block modes, use as stream ciphers
- Stream ciphers: ChaCha20, generation of key streams
- Password-based encryption/decryption
- Key management
- Message digests, MACs, key derivation functions
- Asymmetric cryptography: DH, RSA, DSS, ECDSA
- Methods for developing secure software: e.g.
- Design principles according to Saltzer and Schroeder
- Secure coding guidelines (Java)
- Unit testing when using cryptography
- Penetration testing with software tools
- Best practices (OWASP Top 10, SAMM, ASVS)
The language of instruction is English.
C can be used as an alternative to Java.
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Project work accompanying the lecture with final presentation
- Individual work
- Inverted teaching (inverted classroom)
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- Oral examination
- Project work with oral examination
Requirements for the awarding of credit points
- passed oral examination
- successful project work
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
Literature
- D. Hook und J. Eaves: Java Cryptography: Tools and Techniques, Leanpub, 2023
- F. Long, D. Mohindra, R. C. Seacord, D. F. Sutherland und D. Svoboda: Java Coding Guidelines: 75 Recommendations for Reliable and Secure Programs, Addison-Wesley Professional, 2013
- K. Schmeh: Kryptografie Verfahren - Protokolle - Infrastrukturen, 6. Auflage, dpunkt.verlag, 2016
- R. E. Smith: A Contemporary Look at Saltzer and Schroeder s 1975 Design Principles, IEEE Security & Privacy, 10(6), 20-25, 2012
Gestaltung mit elektronischen Medien- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46825
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
To implement own visual impressions with the help of recording media and programs according to the requirements of IT and internet interfaces. At the same time, to acquire the ability to brief media producers within a production according to the task catalogs.
Taught basic knowledge of the image editing program ADOBE PHOTOSHOP and Windows Paint 3D as an example. Application through practical recording work in a studio atmosphere with visual tools for recording and post-production of videos. Examination of recording media (classic photo and video cameras including current SmartPhone models) for practical suitability for IT and TV.Contents
Illumination of historical sources of the image media photography and video. Technical contexts, development and embedding of these media in computer technology, the processing and application of moving image media within the broad spectrum of information and telecommunication.
Teaching methods
- Lecture in seminar style, with blackboard and projection
- seminar-style teaching with flipchart, smartboard or projection
- Exercise to accompany the lecture
- solving practical exercises in individual or team work
- project work accompanying the lecture with final presentation
- Workshops
- Group work
- Individual work
- Presentation
- Seminar
- Exercises or projects based on practical examples
- Immediate feedback and performance review
- Regular discussion of the interim status of the project or seminar paper with the responsible supervisor
- Concluding presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
Project work with oral examination
Requirements for the awarding of credit points
- passed oral examination
- successful project work
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Medical Informatics Dual
Literature
- Walter Benjamin, Das Kunstwerk im Zeitalter seiner technischen Reproduzierbarkeit, Paris 1935
- Roland Barthes, Die helle Kammer: Bemerkungen zur Photographie , Paris 1980
- Susan Sonntag, On Photography New York 1977
IT-Servicemanagement- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46905
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Transfer of basic knowledge regarding the importance and use of IT service management in the company. Theoretical knowledge of the five phases and their processes, roles and functions of the IT Infrastructure Library (ITIL) lifecycle model. Consolidation and practical application of previously acquired specialist knowledge using practical examples.
Technical and methodological competence:- Distinguishing between IT management and IT service management
- Naming the reasons for and objectives of using ITIL
- Differentiating the different phases of the ITIL lifecycle
- Use case studies to deepen the knowledge gained and develop your own solutions in the ITIL environment
- Design and implement your own ITIL implementation scenarios in exemplary case studies
- Develop detailed processes based on the ITIL phases for specific practical tasks
Interdisciplinary methodological competence:
- Selecting suitable communication structures for service and support processes/structures
- Systematic prioritization of activities and projects
- Knowing error cultures (human factor in stressful situations)
- Evaluating classic conflicts between design and operational functions
- Classification of DevOps and agile development in ITIL phases
- Systematic use of IT KPIs to measure the achievement of objectives
Professional field orientation:
- Knowledge of the requirements of different job profiles in the IT service management environment (service owner, service manager, process owner, process manager, etc.)
- Applying IT processes in the context of IT service management
- Knowing roles and responsibilities within IT service management
- Selecting and using suitable models, concepts and tools
Contents
- IT Management and Business Service Management (BSM) Basics
- Business Process Modeling Notation Basics
- IT service management (ITSM) basics
- Concepts and methods of IT service management
- ITIL basics and history
- ITIL (IT Infrastructure Library) V3 2011
- Service strategy (Service Strategy)
- Service design (Service Design)
- Service Transition (Service Transition)
- Service Operation (Service Operation)
- Continuous Service Improvement
Teaching methods
- Lecture in seminar style, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Case studies
- Role-playing games
- Exercises or projects based on practical examples
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- WXYZ
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- Axelos, ITIL® Service Continual Service Improvement; Edition2011; London TSO; 2013
- Axelos, ITIL® Service Design, Edition 2011; London TSO; 2013
- Axelos, ITIL® Service Operation; Edition 2011; London TSO; 2013
- Axelos, ITIL® Service Strategy; Edition 2011; London TSO; 2013
- Axelos, ITIL® Service Transition; Edition 2011; London TSO; 2013
- Beims, M.; IT-Service Management mit ITIL®, ITIL® Edition 2011, ISO 20000:2011 und PRINCE2® in der Praxis; 3. Auflage; Dr. Carl Hanser Verlag; 2012
- Buchsein, R., Victor, F. Günther, H., Machmeier, V.; IT-Management mit ITIL® V3: Strategien, Kennzahlen, Umsetzung; 2. Auflage; Vieweg; Wiesbaden; 2008
- Olbrich, Al.; ITIL kompakt und verständlich; 4. Auflage; Vieweg; Wiesbaden; 2006
- Victor, F., Günther, H.; Optimiertes IT-Management mit ITIL; 2. Auflage; Vieweg; Wiesbaden; 2005
- Zarnekow, R., Fröschle, H.-P.; Wertorientiertes IT-Servicemanagement: HMD - Praxis der Wirtschaftsinformatik (Heft 264); dpunkt Verlag; Heidelberg; 2008.
Informations- und Business Performance Management- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46909
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
The course is based on business management methods and derives requirements for IT support from them. Based on the consideration of the conceptual level of analytical applications, the technical implementation of the concepts and their comparison with each other is carried out.
Technical and methodological competence (also interdisciplinary):- Knowing and classifying the terms strategic alignment, document management, balanced scorecard, key figure systems and predictive modeling
- Recognize the core concepts of the information supply chain, multidimensional modelling, MOLAP, ROLAP, in-memory, data warehouse and data mining concepts
- Basics of big data processing
- Understanding and applying advanced business management methods such as planning and budgeting
- Knowing and classifying life cycle models, reference models and modeling languages
- Name and differentiate between information architectures
Professional field orientation:
- Application and concrete use of the methods taught in a semester-accompanying project .
- Construction of reports and analysis models from raw data, the use of various life cycle models (Kimball, Inmon, CRISP) based on the implementation of a small business intelligence project in a team.
Social skills:
- Group work strengthens personal social coordination and communication during the event .
- The project organization and management guided by the life phase models provides students with interdisciplinary methodological skills.
Contents
- Overview and introduction
- Chapter I
- Information and decision theory
- Information supply chain
- Business signals
- Operational and analytical applications
- Balanced scorecard
- Chapter II
- Accounting, controlling, strategic planning
- Extraction, transformation, loading (ETL)
- Concept of the data warehouse
- Multidimensional modeling
- Chapter III
- Predictive analytics, data mining methods and applications
- Chapter IV
- Big data and document management
- Chapter V
- Multidimensional business applications
- OLAP analysis
- Business planning
- Group consolidation
- Chapter VI
- Case studies of analytical applications
- Chapter VII
- Strategic Business and IT Alignment
- Lifecycle models for information management projects
Semester-accompanying group project:
Development of a reporting system for standard and OLAP reports based on tourism market research data using Microsoft SQL Business Intelligence Studio with the following sub-steps:
- Understanding the question
- Understanding the data
- Processing the data
- Modeling
- Validation
- Application
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Solving practical exercises in individual or team work
- Internship accompanying the lecture
- Group work
- Concluding presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written examination paper 75%
- semester-accompanying coursework 25%
Requirements for the awarding of credit points
- passed written examination
- successful presentation
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science
Literature
- Bashiri, I., Engels, C., Heinzelmann, M., Strategic Alignment, Springer, 2010.
- Cameron, S., SQL Server 2008 Analysis Services Step by Step, Microsoft Press, 2009, ISBN-10: 0-7356-2620-0.
- CRISP-DM, 1.0 step-by-step data mining guide, CRISP-DM consortium, 1999, (abgerufen am 25.11.2010) http://www.crisp-dm.org/download.htm.
- Engels, C., Basiswissen Business Intelligence, W3L Verlag, Witten 2009.
- Heinrich, Lutz J.: Informationsmanagement. Seit 1985 im Oldenbourg Wissenschaftsverlag, München / Wien, 8. Aufl. 2005, 9. Aufl. 2009 (1. bis 3. und ab 8. Aufl. mit Ko-Autor), ISBN 3-486-57772-7.
- Jiawei Han, M.Kamber, Data Mining: Concepts and Techniques, http://www.cs.sfu.ca/~han/bk/.
- Robert S. Kaplan, David P. Norton: Balanced Scorecard. Strategien erfolgreich umsetzen. Stuttgart 1997, ISBN 3-7910-1203-7.
- Kemper et.al., Business Intelligence, Vieweg, 3. Auflage, 2010, ISBN 978-3-8348-0719-9.
- Kimball, R. et. al., The Kimball Group Reader, Wiley, 2010.
- Kimball, R., Caserta J., The Data Warehouse ETL Toolkit, Wiley, 2004.
- Krcmar, H.: Informationsmanagement. 6. Auflage, Springer, Berlin et al., 2015, ISBN 978-3-662-45862-4
- Misner, S., SQL Server 2008 Reporting Services Step by Step, Microsoft Press, 2009, ISBN-10: 0-7356-2647-2.
- Mitchell, T., Machine Learning, McGraw Hill, 1997.
- Scheuch, R., Gansor, T., Ziller, C: Master Data Management: Strategie, Organisation, Architektur, dpunkt.verlag, 2012.
- Plattner, H., Zeier, A.: In-Memory Data Management: An Inflection Point for Enterprise Applications, Springer, Berlin, 2011.
Informationssysteme im Gesundheitswesen- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
44441
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- students are able to describe the structure of an electronic patient record and know the differences and areas of application of ePA, eFA, eGA
- the students know the basics of medical information systems and can apply them to specific examples
- they can name the modules of hospital information systems and practice systems and know the main processes supported
- the students are able to parameterize an information system
- they can name the structure and areas of application of HL7, DICOM and IHE
- they know the structure of the telematics infrastructure (TI) and applications on the TI
- they know the legal framework
- they know available and future applications of eHealth in order to optimally support business and clinical processes in the healthcare sector
Social skills:
- They know the essential soft factors in the use of IT in healthcare
Professional field orientation:
- they know the major providers of hospital information systems and their use
- they know what types of information systems are available on the market
- they know the common communication standards and terminology in the professional field of medical informatics
Contents
- Basics of medical information systems
- Structure and concepts of electronic patient records and other record systems
- Modules and supported core processes of a hospital information system
- Functions and supported core processes of a medical practice system
- Basics of communication standards in healthcare such as HL7 FHIR, DICOM, IHE, openEHR (syntactic interoperability)
- Fundamentals of basic terminologies such as ICD, OPS, SNOMED-CT (semantic interoperability)
- Legal framework conditions (KHZG, E-Health Act, DVG, ...)
- Development of the telematics infrastructure and applications on it (DiGAs, teleconsultations, KIM and others)
- Example applications of eHealth: eGK, ePrescription, eMedication, health portal, telemedicine, eDocumentation
- Parameterization of a hospital information system (exercise)
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Excursion
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
Literature
- Krankenhausinformationssystem iMedOne von Tieto (steht im Labor zur Verfügung) mit entsprechenden Handbüchern
- Krankenhausinformationssystem M-KIS der Meierhofer AG (steht im Labor zur Verfügung) mit entsprechenden Handbüchern
- P. Haas; Medizinische Informationssysteme und Elektronische Krankenakten; Springer 2004
- C. Johner; Basiswissen Medizinische Software; DPunkt 2011
Kooperative Systeme- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46912
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- Students know the basics of social groups and how they are supported by technical systems
- The students are able to select, adapt and introduce a specific system for group work in a company
- The importance and impact of IT support for group work in companies is known
Interdisciplinary methodological competence:
- The concepts of group work learned can be used across disciplines
- Students can assess the importance of cooperative systems for the IT landscape of a company
Social competence:
- The seminar accompanying performance is carried out as group work and thus promotes social competence .
- This is supported by the application of the concepts learned in this course on the topic of groups
Contents
- Theoretical foundations: social groups, communication, cooperation, coordination, knowledge management
- Technical implementation of cooperative systems: classifications and components
- Current examples from CSCW, CSCL, knowledge management, Web 2.0, social networks
- Cooperative systems for companies: Importance, selection, customization, implementation, impact
Teaching methods
Seminar-style teaching with flipchart, smartboard or projection
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- Homework
- Presentation
- Semester-accompanying coursework (bonus points)
Requirements for the awarding of credit points
- successful term paper
- successful presentation
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- Back, A.; Gronau, N.; Tochtermann, K. (2012): Web 2.0 und Social Media in der Unternehmenspraxis: Grundlagen, Anwendungen und Methoden mit zahlreichen Fallstudien.München: Oldenbourg, 3. Auflage.
- Gross, T.; Koch, M. (2007): Computer Supported Cooperative Work. München: Oldenbourg.
- Haake, J. M.; Schwabe, G.; Wessner, M. (Hrsg.) (2012): CSCL-Kompendium. München: Oldenbourg Verlag, 2. Auflage.
- Koch, M.; Richter, A. (2008): Enterprise 2.0: Planung, Einführung und erfolgreicher Einsatz von Social Software in Unternehmen. München: Oldenbourg.
- Schwabe, G.; Streitz, N.; Unland, R. (2001): CSCW-Kompendium: Lehr- und Handbuch Zum Computerunterstützten Kooperativen Arbeiten.Heidelberg: Springer.
Mobile App Engineering- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46847
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- Know, understand and assess the technical software challenges involved in developing mobile apps
- Know and be able to apply processes, activities, methods, techniques, languages and tools for mobile app-specific requirements engineering
- Know and be able to apply processes, activities, methods, techniques, languages and tools for designing mobile apps
- Know and be able to apply processes, activities, methods, techniques, languages and tools for designing the interaction options and screen pages of a mobile app
- Know and be able to apply processes, activities, methods, techniques, languages and tools for implementing mobile apps
- Know and be able to apply processes, activities, methods, techniques, languages and tools for testing mobile apps
- Know and be able to apply processes, activities, methods, techniques, languages and tools for going live with mobile apps
- Know and be able to apply processes and activities, roles and responsibilities in the field of mobile app engineering
Self-competence:
- Development and creation of mobile app-specific development and results documents
- Independent development of a mobile app across all development phases: from requirements to go-live
- Presentation of the developed and achieved results
Social skills:
- Teamwork in groups of four in the internship over an entire semester
Professional field orientation:
- Practical implementation of mobile app-specific processes and activities
- Practical application of mobile app-specific methods, techniques, languages and tools
Contents
The aim and content of the course is to teach suitable methods, concepts, techniques, languages and tools to professionally conceptualize, design, develop, test and commission mobile business apps from a software engineering perspective. The entire life cycle of a mobile app is considered, including:
- User-oriented collection and specification of the functional and non-functional requirements for a mobile app
- GUI prototyping with low- and high-fidelity prototypes
- UX/UI design,
- Specification of the interaction design and the individual screen pages,
- Implementation of mobile apps,
- Testing of mobile apps
- Processes and activities for the go-live of a mobile app
The phases and activities to be carried out are described and illustrated in a practical way using suitable methods, techniques, languages and tools based on a large industrial mobile app development project.
In the practical part of the course, selected requirements, conception, design, development and testing activities are carried out in teamwork in order to develop a mobile app independently.
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Solving practical exercises in individual or team work
- Internship accompanying the lecture
- Processing programming tasks on the computer in individual or team work
- Concluding presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Business Informatics
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor of Medical Informatics
- Bachelor of Computer Science Dual
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- Vollmer, G. (2017): Mobile App Engineering, Heidelberg: dpunkt-Verlag.
Modellbasierte Softwareentwicklung- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46897
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
After completing the course, students will be able to
- Create models of software systems and technical systems .
- create software automatically with the help of models. Design a domain-specific language (DSL), implement it textually or graphically and provide tool support.Enrich a DSL with constraints to ensure the well-formedness of models
- Construct transformations and simple code generators .
- Select suitable technologies for modeling and generation
Contents
- Basics: model concept, model building, perspectives and levels of abstraction
- Modeling in software engineering and technical systems
- Metamodeling, four-level meta-modeling architecture, linguistic vs. ontological metamodels
- Domain-specific languages
- textual
- graphical
- Architecture, target platform, transformation and code generation
- Model-driven software development
- with Eclipse Modeling Framework/Ecore
- with Xtext, Xpand and Xtend, more recent developments
- with UML and related technologies: UML, Object Constraint Language (OCL), Query View Transformation Language (QVT)
- with MPS (JetBrains)
- Reference to related topics: e.g. product lines, quality assurance/testing
- Case studies from the areas of desktop, mobile and embedded systems (e.g. mbeddr)
Teaching methods
Lecture in seminar style, with blackboard writing and projection
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
Project work with oral examination
Requirements for the awarding of credit points
Successful project work
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Computer Science Dual
Literature
- Völter: "DSL Engineering", dslbook.org, 2013
- Völter: "Generic Tools, Specific Languages", 2014
- Steinberg: EMF: Eclipse Modeling Framework (2nd Edition), Addison-Wesley, 2008
- Gronback: Eclipse Modeling Project A Domain-specific Language (DSL) Toolkit , Addison-Wesley, 2009
- Stahl, Völter, Efftinge, Haase: Modellgetriebene Softwareentwicklung , dpunkt.verlag, 2. Auflage, 2007
- Gruhn, Pieper, Röttgers: MDA , Springer, 2006
- Markus Völter, DSL Engineering: Designing, Implementing and Using Domain-Specific Languages, dslbook.org, 2013
Moderne Datenbanken- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46892
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Expert knowledge:
- Know and use NoSQL database models and demonstrate possible applications .
- Know and explain materialized and virtual information integration.
- Know and explain distributed database architectures for big data applications. Know and explain exemplary data streaming applications.
- Evaluate big data applications taking into account ethical, social and Business Studies aspects.
Social competence:
- Developing, communicating and presenting non-relational database applications in small groups .
- Collaboratively creating and comparing non-relational database applications with relational solutions
Professional field orientation:
- Know the requirements of different job profiles in the database environment (database administrator. Database developer, application developer, data protection officer) .
Contents
- Distributed databases and big data applications
- Architectures for data streaming applications
- NoSQL database models
- Selected algorithms (e.g. map-reduce algorithm)
- Current applications
Teaching methods
- Seminar-style teaching with flipchart, smartboard or projection
- Processing programming tasks on the computer in individual or team work
- Project work accompanying the lecture with a final presentation
- Group work
- active, self-directed learning through internet-supported tasks, sample solutions and accompanying materials
- homework to accompany the course
- the lecture is offered as a video
- Inverted teaching (inverted classroom)
- Concluding presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written exam paper
- presentation
- examinations during the semester
Requirements for the awarding of credit points
- passed written examination
- successful presentation
- successful mini-project (project-related work)
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science
Literature
- S. Edlich, A. Friedland, J. Hampe, B. Brauer, NoSQL Einstieg in die Welt nichtrelationaler Web 2.0 Datenbanken, Hanser Verlag 2010
- M. Kleppmann, Designing data-intensive applications, O'Reilly Media (2017)
- A. Bifet, Machine learning for data stream, MIT-Press (2017)
- B. Ellis, Real-time analytics, Wiley & Sons (2014)
- Aktuelle Fachliteratur
Multimedia- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
43082
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
The students should be able to work on the creation of IT-supported media products. This includes both classic media-based multimedia products, such as DVDs, as well as web-based offerings. For this purpose, the necessary basics for an understanding of today's common media technologies are taught. This ranges from developing your own filters for image processing to raising awareness of the special legal framework conditions when using media in software products.
Technical and methodological skills:
- SW-technical implementation of basic image processing algorithms
- Naming important media file formats and their properties
- Creating the Huffman coding for a given message source
- Calculating the entropy of a message source
- Conversion between color models
- SW-technical implementation of basic graphic algorithms, such as floodfill
Social skills:
- Working on the exercises in small groups of 2-4 students
- Programming in pairs
Professional field orientation:
- Providing basic knowledge for IT media projects
Contents
1. basics
- History
- Information technology
- Information theory
- Compression & coding
2. graphics & font
- Perception
- Color models
- Graphic formats
- Typography
- Font formats & character sets
3. audio
- Basics
- Language
- Data formats
4. video & animation
- Basics
- Analog & digital technology
- Real-time graphics
5. interdisciplinarity
- Media engineering
- Development processes
- Ethics of digital media
- Law in media informatics
6. further content
In consultation with the students, one to three of the following topics will be covered. The list will be expanded as required
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- Project work with oral examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
- passed written examination
- passed oral examination
- successful project work
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor of Computer Science
Literature
Literaturhinweise werden in der Veranstaltung bekanntgegeben.
Die im jeweiligen Semester eingesetzte Prüfungsform (z.B. mündliche Prüfung) wird zu Beginn der Veranstaltung bekanntgegeben. Dies gilt ebenfalls für eine möglicherweise genutzte Bonuspunkteregelung.
Numerische Algorithmen- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46840
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Teaching the fundamentals, techniques and algorithms of numerical and applied mathematics, insofar as they are relevant to the successful study of computer science. Students should be familiar with the specified course content and be able to make informed decisions about which technique to use to solve which problem. Furthermore, they should be introduced to the efficient implementation of the algorithms presented with the help of Matlab and be able to develop these further independently.
Technical and methodological skills:
- Calculation of numerical representations
- Analysis of numerical errors
- Numerical calculation of fixed points, zeros and roots
- Numerical calculation of derivatives and integrals
- Numerical solution of linear systems of equations
- Numerical solution of eigenvalue and eigenvector problems
- Calculation of approximating and interpolating polynomials and splines
- Calculation of approximating and interpolating surfaces
Contents
- Number representations and error analysis
- LR decomposition
- QR decomposition (Givens and Householder)
- Cholesky decomposition
- Banach's fixed point theorem
- Newton method
- Heron method
- Secantal method
- Descent method
- Divided-difference method
- Trapezoidal and Simpson's rule
- Norms and sequences in multidimensions
- Total step, single step and SOR methods
- Von Mises-Geiringer method
- Polynomial interpolation and approximation
- Spline interpolation and approximation
- Trigonometric interpolation and DFT
- Bilinear interpolation
- Multidimensional polynomial approximation
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Active, self-directed learning through tasks, sample solutions and accompanying materials
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- R. Schröder: Numerische Algorithmen, Skript zur Vorlesung.
Ergänzend:
- G, Bärwolf, Numerik für Ingenieure, Physiker und Informatiker, Springer-Verlag, Berlin-Heidelberg-New York, 2017, dritte Auflage
- G. Farin, Curves and Surfaces for CAGD, Academic Press, San Diego, 2002, fünfte Auflage.
- M. Hermann, Numerische Mathematik, de Gruyter-Oldenbourg, 2011, dritte Auflage
- T. Huckle, S. Schneider, Numerik für Informatiker, Springer-Verlag, Berlin-Heidelberg-New York, 2006, zweite Auflage.
- B. Lenze, Basiswissen Angewandte Mathematik, W3L-Verlag, Dortmund, 2014, erster Nachdruck.
- H. Prautzsch, W. Boehm, M. Paluszny, Bezier and B-Spline Techniques, Springer-Verlag, Berlin-Heidelberg-New York, 2010, erster Nachdruck.
- R. Schaback, H. Wendland, Numerische Mathematik, Springer-Verlag, Berlin-Heidelberg-New York, 2005, fünfte Auflage.
- J. Werner, Numerische Mathematik 1 und 2, Vieweg, Wiesbaden, 1992
Rechnerarchitekturen- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46845
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- knows the various basic architectures for digital computer architectures
- can identify and classify the individual architecture elements
- can analyze application scenarios and select suitable architecture features
- knows the entire range from the structure level (RTL) to the instruction set level (ISA) and can apply these
- can understand and apply architecture manuals and instruction set manuals of current computer architectures
- Optimization options for computer architectures (e.g. caching, jump prediction) are understood and can be assessed
- knows paradigms such as parallel processing and special areas such as architectures for embedded systems through exemplary insights
- can assess and select microcontrollers with regard to their area of application and program them close to the hardware in assembler and C
- can use a development environment (using the Keil uVision environment as an example)
- can analyze current computer architectures and evaluate and discuss them against the background of their knowledge
Contents
- Structure and function of the Turing machine as an introductory example of a very rudimentary computer architecture => identification of the basic components arithmetic unit/control unit/memory/instruction set
- Structure and function of the integer Java virtual machine according to Tanenbaum
- Instruction set (ISA) and microcode, optimization of microcode, explanation of the specifics of ISA in Java byte code, CISC, RISC
- Analysis and optimization of the processing pipeline, instruction fetch unit, jump prediction, speculative execution, out-of-order execution
- Analysis of memory architecture, caching, memory types (SDRAM, graphics DRAM, SRAM, flash) and architectures .
- Comparative analysis of Intel Core and Intel Netburst architecture with regard to the above-mentioned topics
- Parallel computer architectures, including cache coherence (especially MESI), VLIW
- Examples of special computers (mobile processors, data flow computers)
- Architectures for embedded systems (including ARM, introduction of DMA and interrupt units)
- Atmel AVR as an example for microcontrollers, architecture, ISA, assembler and C programming
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
- Processing programming tasks on the computer in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Medical Informatics
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- Tanenbaum, A.: Computerarchitektur, 5. Auflage, Pearson, 2006
- Yiu, J.: The Definitive Guide to the ARM Cortex M0, Newnes, Elsevier, 2011
- Martin, T.: The Designer's Guide to the Cortex-M Processor Family, Newnes, Elsevier, 2013
- Brinkschulte, U.; Ungerer, T.: Mikrocontroller und Mikroprozessoren, 3. Auflage, Springer, 2010
Robotik- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46855
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
After completing the lecture, students will be able to
- Understand and apply methods and concepts of robotics
- design and implement stationary and mobile robotics applications
- set up kinematic equations for mobile and stationary robots
- select components for robotics applications
- configure and program mobile and stationary robots
Contents
- Objectives and areas of application of robotics
- Design of stationary and mobile robots
- Kinematics of stationary robots
- Applications of stationary robots
- Subsystems of robots (joints, drives, actuators and sensors)
- Kinematics of mobile wheel-driven robots
- Self-localization and navigation of mobile robots
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Solving practical exercises in individual or team work
- Internship accompanying the lecture
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor of Computer Science
Literature
- Corke, Peter: Robotics, Vision and Control: Fundamental Algorithms in MATLAB, second edition, Springer, 2017
- Weber, Wolfgang: Industrieroboter: Methoden der Steuerung und Regelung, Carl Hanser Verlag, 3. Auflage, 2017
- Siegwart, Roland; Nourbakhsh, Illah R.: Introduction to Autonomous Mobile Robots, MIT Press, 2nd Edition, 2011
- Hesse, Stefan; Malisa, Viktorio (Hrsg.): Taschenbuch Robotik - Montage - Handhabung, Carl Hanser Verlag, 2010
- Hertzberg, Joachim; Lingemann, Kai; Nüchter, Andreas: Mobile Roboter - Eine Einführung aus Sicht der Informatik, Springer Vieweg Verlag, 2012
Softwaretechnik C (Softwaremanagement)- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
45261
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
- Be able to assess and evaluate the complexity of software projects
- Analyzing the background and causes of project failures
- Know software development procedure and process models and be able to select them for specific contexts
- Waterfall and spiral model, prototyping, V-model XT, Rational Unified Process, agile models (Scrum)
- Know and be able to apply processes and activities, roles and responsibilities in the area of software management
Interdisciplinary methodological competence:
- Be able to organize and manage software projects
- Project planning, effort estimation, effort and cost controlling
- Know product management
- Know and be able to apply process analysis, measurement and evaluation
- Improvement of process quality (CMMI, GQM)
Self-competence:
- Development and creation of software management-specific result documents
- Independent creation and presentation of selected software management topics and content
Social skills:
- Teamwork in groups of four over an entire semester
Professional field orientation:
- Practical application and implementation of software management-specific processes and activities
Contents
- Procedure and process models of software engineering (waterfall, concurrent and spiral model, V-Modell XT, Rational Unifed Process, Scrum)
- Know and be able to apply processes and activities, concepts and methods of requirements management
- Know and be able to apply risk management processes and activities, concepts and methods
- Know and be able to apply project management (planning and control) processes and activities, concepts and methods
- Know and be able to apply quality management processes and activities, concepts and methods
- Know and be able to apply configuration management processes and activities, concepts and methods
- Know and be able to apply product management processes and activities, concepts and methods
- Know and be able to apply release management processes and activities, concepts and methods
- Know and be able to apply processes and activities, concepts and methods of process improvement
- Know and be able to apply framework models for process improvement
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Exercise accompanying the lecture
- Solving practical exercises in individual or team work
- Internship accompanying the lecture
- Group work
- Exercises or projects based on practical examples
- immediate feedback and performance review
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Business Informatics
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Computer Science Dual
- Bachelor of Computer Science Dual
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- Balzert, H. (2008): Lehrbuch der Softwaretechnik: Softwaremanagement, 2. Auflage, Heidelberg: Spektrum Akademischer Verlag.
- Balzert, H. (2009): Basiskonzepte und Requirements Engineering, 3. Auflage, Heidelberg: Spektrum Akademischer Verlag.
- Ludewig, J., Lichter, H. (2013): Software Engineering Grundlagen, Menschen, Prozesse, Techniken, 3. korrigierte Auflage, Heidelberg: dpunkt-Verlag.
- Pichler, R. (2009): Scrum - Agiles Projektmanagement erfolgreich einsetzen, Heidelberg: dpunkt-Verlag.
- Pohl, K.; Rupp, C. (2015): Basiswissen Requirements Engineering, 4. überarbeitete Auflage, Heidelberg: dpunkt-Verlag.
- Sommerville, I. (2018): Software Engineering, 10. aktualisierte Auflage, München: Pearson.
- Spitzcok, N.; Vollmer, G., Weber-Schäfer, U. (2014): Pragmatisches IT-Projektmanagement, 2. aktualisierte und überarbeitete Auflage, Heidelberg: dpunkt-Verlag.
- Vollmer, G. (2017): Mobile App Engineering, Heidelberg: dpunkt-Verlag.
- Vollmer, G. (WS 2019/2020): Unterlagen zur Lehrveranstaltung "Softwaretechnik C - Softwaremanagement".
- Winkelhofer, G. (2005): Management- und Projekt-Methoden, 3. Auflage, Berlin, Heidelberg: Springer.
Softwaretechnik D (Qualitätssicherung und Wartung)- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46264
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Teaching the knowledge required to achieve a defined level of quality in software development. The analytical and constructive measures for quality assurance are known and can be applied in a targeted manner. Methodical approach to software maintenance.
Technical and methodological competence:
- Differentiating between analytical and constructive measures for quality assurance
- Naming typical sources of error
- Selecting suitable tools in the context of constructive software engineering
- Selecting suitable metrics for quality measurement
- Knowing different integration strategies
- Recognizing the influence of automation on quality
- Systematically derive test cases
- Performing manual test procedures
- Applying analytical test procedures
- Naming risks, problems and principles of maintenance
- Organizing software maintenance
Interdisciplinary methodological competence:
- Operationalizing the concept of quality via quality models
- Understanding that testing is a necessary but not sufficient measure to ensure quality
- Conducting target group-oriented presentations
Professional field orientation:
- Creating a quality manual
- Selecting and using suitable tools (constructive software engineering)
Contents
- Quality models
- Sources of error
- Constructive measures
- Manual test methods
- Tools
- Black box test
- White box test
- Metrics
- Static code analysis
- Test management
- Automation (software infrastructure)
- Load test
- Maintenance and care
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Business Informatics
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Computer Science Dual
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- Balzert, H.; "Lehrbuch der Softwaretechnik, Softwaremanagement", Spektrum Akademischer Verlag, Heidelberg, 2008
- Binder, R.V.; "Testing Object-Oriented Systems", Addison-Wesley, Boston, 2000
- Hoffmann, D.W.; "Software-Qualität", Springer Vieweg, Berlin, 2013
- Liggesmeyer, P.; "Software-Qualität", Spektrum Akademischer Verlag, Heidelberg, 2009
- Ludewig, J.; Lichter, H.; "Software Engineering", dpunkt.verlag, Heidelberg, 2010
- Spillner, A.; Linz, T.; "Basiswissen Softwaretest", dpunkt.verlag, Heidelberg, 2012
- Sneed, H.M.; Seidl, R.; Baumgartner, M.; "Software in Zahlen", Hanser, München, 2010
Systemprogrammierung- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46849
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Technical and methodological competence:
Knowledge:
- Fundamental concepts of operating systems
- Functionality of linkers and loaders
- Principles for debugging user programs
- Concepts of the Java VM and dynamic memory management
Application:
- Concurrent programming under Java
- Using the methods of the Java Runtime, Thread and ClassLoader classes
- Using synchronous and asynchronous communication
Contents
- Selected topics from the field of operating systems (linkers and loaders, runtime environment, memory management, mutual exclusion, deadlocks, concurrent programming, scanners, parsers)
- Selected topics from the field of distributed systems (synchronous and asynchronous communication, clock synchronization) Selected topics from the field of hardware-related programming (data types and basic operations, interrupts)
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science
Literature
- A. Silberschatz, P. Galvin: Operating System Concepts, John Whiley & Sons, 2008 (8th Edition)
- Andrew S. Tanenbaum: Computernetzwerke, Pearson Studium, München 2003
- Andrew S. Tanenbaum: Moderne Betriebssysteme, Pearson Studium, München 2009
Virtualisierung und Cloud Computing- WP
- 4 SWS
- 5 ECTS
- WP
- 4 SWS
- 5 ECTS
Number
46810
Language(s)
en
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
Providing basic knowledge in the field of virtualization and cloud computing. Theoretical knowledge of architectures and technologies in this area and awareness of their strengths and weaknesses in various areas of application. Consolidation of specialist knowledge using practical laboratory tasks with currently relevant cloud services and technology platforms.
Technical and methodological expertise:- Learning the relevant technical terms in the field of virtualization and cloud computing
- Classification and evaluation of the various concepts and architectures
- Installation and configuration of simple virtual systems with different technologies
- Conception and practical setup of simple cloud services with open-source and commercial resource management systems
- Overview of traditional and new areas of application for virtualization and cloud computing
- Overview of current research topics and evaluation of scientific publications
Contents
- Virtualization of CPU, memory and network components
- Container technology
- Current virtualization and container platforms
- Resource management and orchestration
- Current resource management and orchestration platforms
- Cloud computing service models (IaaS, PaaS etc.)
- New areas of application for virtualization and cloud computing (edge computing, NFV etc.)
- Open source development processes and communities
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Processing programming tasks on the computer in individual or team work
- Project work accompanying the lecture with final presentation
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
- written written examination
- study achievements during the semester (bonus points)
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor's degree in Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science
Literature
- Thomas Erl, Zaigham Mahmood, Ricardo Puttini; Cloud Computing; Prentice Hall; 2013
- K. Chandrasekaran; Essentials of Cloud Computing; CRC Press; 2015
6. Semester of study
Informationssicherheit- PF
- 4 SWS
- 5 ECTS
- PF
- 4 SWS
- 5 ECTS
Number
46813
Language(s)
de
Duration (semester)
1
Contact time
60 h
Self-study
90 h
Learning outcomes/competences
The students are able to
- define, differentiate and explain basic information security terminology
- understand the central importance of standardization in information security and map it methodically. to independently view and analyze information about vulnerabilities and threats and make informed decisions based on this information.explain and apply organizational and technical security measures.
Contents
- Terminology
- IT security, information security, difference between security and safety
- System, fact, assumption, asset
- Protection objective (CIA and authentication)
- Vulnerability, vulnerability, threat, attack, attacker types
- Risk
- Security objective, security requirement
- Security measure
- Human factor, security awareness
- Legal framework, European General Data Protection Regulation
- Standards and best practices
- ISO/IEC 27000 series
- IT baseline protection
- OWASP
- Applied cryptography
- Symmetric encryption (basics, AES, block modes, padding, pitfalls)
- Hash functions (types of attack, SHA-2 family, SHA-3 family), MAC
- Asymmetric cryptography (basics, DH, RSA, ECC, padding, pitfalls, digital shelf marks, certificates)
- Access control
- Basics (DAC, MAC, RBAC, Deny by Default, Least Privilege)
- Advanced models (ABAC, ReBAC), modeling
- Authentication
- Basics of authentication (types, MFA, entropy)
- Password-based authentication (Linux password databases, types of attacks, Salt, Argon2, NIST 800-63B)
- Basics of software development and information security
- Asset identification and analysis
- Threat modeling
- Best practices (OWASP Top 10, SAMM, ASVS, Testing Guide)
- Penetration testing
Teaching methods
- Lecture in interaction with the students, with blackboard writing and projection
- Solving practical exercises in individual or team work
Participation requirements
See the respective valid examination regulations (BPO/MPO) of the study program.
Forms of examination
written exam paper
Requirements for the awarding of credit points
passed written exam
Applicability of the module (in other degree programs)
- Bachelor of Business Informatics
- Bachelor of Software and Systems Engineering (dual)
- Bachelor of Computer Science
- Bachelor of Computer Science
- Bachelor's degree in Medical Informatics
- Bachelor of Medical Informatics Dual
- Bachelor of Computer Science Dual
- Bachelor of Computer Science Dual
Literature
- R. Anderson: Security Engineering: A Guide to Building Dependable Distributed Systems, 3. Auflage, John Wiley & Sons Inc., 2020
- C. Eckert: IT Sicherheit (Konzepte, Verfahren, Protokolle), 11. Auflage, De Gruyter Oldenbourg, 2023
- ISO/IEC 27000: Information technology Security techniques Information security management systems Overview and vocabulary, 2018
- K. Schmeh: Kryptografie Verfahren - Protokolle - Infrastrukturen, 6. Auflage, dpunkt.verlag, 2016
Thesis mit Kolloquium- PF
- 0 SWS
- 15 ECTS
- PF
- 0 SWS
- 15 ECTS
Number
103
Duration (semester)
1