Program description
Content
Core Qualification
Module M0561: Discrete Algebraic Structures 

Courses  

Module Responsible  Prof. KarlHeinz Zimmermann 
Admission Requirements  None 
Recommended Previous Knowledge 
Mathematics from High School. 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
The students know the important basics of discrete algebraic structures including elementary combinatorial structures, monoids, groups, rings, fields, finite fields, and vector spaces. They also know specific structures like sub. sum, and quotient structures and homomorphisms. 
Skills 
Students are able to formalize and analyze basic discrete algebraic structures. 
Personal Competence  
Social Competence 
Students are able to solve specific problems alone or in a group and to present the results accordingly. 
Autonomy 
Students are able to acquire new knowledge from specific standard books and to associate the acquired knowledge to other classes. 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  120 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory Computer Science: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Orientierungsstudium: Core Qualification: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory 
Course L0164: Discrete Algebraic Structures 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. KarlHeinz Zimmermann 
Language  DE 
Cycle  WiSe 
Content  
Literature 
Course L0165: Discrete Algebraic Structures 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. KarlHeinz Zimmermann 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0731: Functional Programming 

Courses  

Module Responsible  Prof. Sibylle Schupp  
Admission Requirements  None  
Recommended Previous Knowledge  Discrete mathematics at highschool level  
Educational Objectives  After taking part successfully, students have reached the following learning results  
Professional Competence  
Knowledge 
Students apply the principles, constructs, and simple design techniques of functional programming. They demonstrate their ability to read Haskell programs and to explain Haskell syntax as well as Haskell's readevalprint loop. They interpret warnings and find errors in programs. They apply the fundamental data structures, data types, and type constructors. They employ strategies for unit tests of functions and simple proof techniques for partial and total correctness. They distinguish laziness from other evaluation strategies. 

Skills 
Students break a naturallanguage description down in parts amenable to a formal specification and develop a functional program in a structured way. They assess different language constructs, make conscious selections both at specification and implementations level, and justify their choice. They analyze given programs and rewrite them in a controlled way. They design and implement unit tests and can assess the quality of their tests. They argue for the correctness of their program. 

Personal Competence  
Social Competence 
Students practice peer programming with varying peers. They explain problems and solutions to their peer. They defend their programs orally. They communicate in English. 

Autonomy 
In programming labs, students learn under supervision (a.k.a. "Betreutes Programmieren") the mechanics of programming. In exercises, they develop solutions individually and independently, and receive feedback. 

Workload in Hours  Independent Study Time 96, Study Time in Lecture 84  
Credit points  6  
Course achievement 


Examination  Written exam  
Examination duration and scale  90 min  
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L0624: Functional Programming 
Typ  Lecture 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. Sibylle Schupp 
Language  EN 
Cycle  WiSe 
Content 

Literature 
Graham Hutton, Programming in Haskell, Cambridge University Press 2007. 
Course L0625: Functional Programming 
Typ  Recitation Section (large) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. Sibylle Schupp 
Language  EN 
Cycle  WiSe 
Content 

Literature 
Graham Hutton, Programming in Haskell, Cambridge University Press 2007. 
Course L0626: Functional Programming 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. Sibylle Schupp 
Language  EN 
Cycle  WiSe 
Content 

Literature 
Graham Hutton, Programming in Haskell, Cambridge University Press 2007. 
Module M0575: Procedural Programming 

Courses  

Module Responsible  Prof. Siegfried Rump 
Admission Requirements  None 
Recommended Previous Knowledge 
Elementary PC handling skills Elementary mathematical skills 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
The students acquire the following knowledge:

Skills 

Personal Competence  
Social Competence 
The students acquire the following skills:

Autonomy 

Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  90 minutes 
Assignment for the Following Curricula 
Computer Science: Core Qualification: Compulsory Electrical Engineering: Core Qualification: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory Mechatronics: Core Qualification: Compulsory Orientierungsstudium: Core Qualification: Elective Compulsory Technomathematics: Core Qualification: Compulsory 
Course L0197: Procedural Programming 
Typ  Lecture 
Hrs/wk  1 
CP  2 
Workload in Hours  Independent Study Time 46, Study Time in Lecture 14 
Lecturer  Prof. Siegfried Rump 
Language  DE 
Cycle  WiSe 
Content 

Literature 
Kernighan, Brian W (Ritchie, Dennis M.;) Sedgewick, Robert Kaiser, Ulrich (Kecher, Christoph.;) Wolf, Jürgen 
Course L0201: Procedural Programming 
Typ  Recitation Section (large) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Prof. Siegfried Rump 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L0202: Procedural Programming 
Typ  Practical Course 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Siegfried Rump 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0577: Nontechnical Courses for Bachelors 
Module Responsible  Dagmar Richter 
Admission Requirements  None 
Recommended Previous Knowledge  None 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
The Nontechnical
Academic Programms (NTA) imparts skills that, in view of the TUHH’s training profile, professional engineering studies require but are not able to cover fully. Selfreliance, selfmanagement, collaboration and professional and personnel management competences. The department implements these training objectives in its teaching architecture, in its teaching and learning arrangements, in teaching areas and by means of teaching offerings in which students can qualify by opting for specific competences and a competence level at the Bachelor’s or Master’s level. The teaching offerings are pooled in two different catalogues for nontechnical complementary courses. The Learning Architecture consists of a crossdisciplinarily study offering. The centrally designed teaching offering ensures that courses in the nontechnical academic programms follow the specific profiling of TUHH degree courses. The learning architecture demands and trains independent educational planning as regards the individual development of competences. It also provides orientation knowledge in the form of “profiles” The subjects that can be studied in parallel throughout the student’s entire study program  if need be, it can be studied in one to two semesters. In view of the adaptation problems that individuals commonly face in their first semesters after making the transition from school to university and in order to encourage individually planned semesters abroad, there is no obligation to study these subjects in one or two specific semesters during the course of studies. Teaching and Learning Arrangements provide for students, separated into B.Sc. and M.Sc., to learn with and from each other across semesters. The challenge of dealing with interdisciplinarity and a variety of stages of learning in courses are part of the learning architecture and are deliberately encouraged in specific courses. Fields of Teaching are based on research findings from the academic disciplines cultural studies, social studies, arts, historical studies, migration studies, communication studies and sustainability research, and from engineering didactics. In addition, from the winter semester 2014/15 students on all Bachelor’s courses will have the opportunity to learn about business management and startups in a goaloriented way. The fields of teaching are augmented by soft skills offers and a foreign language offer. Here, the focus is on encouraging goaloriented communication skills, e.g. the skills required by outgoing engineers in international and intercultural situations. The Competence Level of the courses offered in this area is different as regards the basic training objective in the Bachelor’s and Master’s fields. These differences are reflected in the practical examples used, in content topics that refer to different professional application contexts, and in the higher scientific and theoretical level of abstraction in the B.Sc. This is also reflected in the different quality of soft skills, which relate to the different team positions and different group leadership functions of Bachelor’s and Master’s graduates in their future working life. Specialized Competence (Knowledge) Students can

Skills 
Professional Competence (Skills) In selected subareas students can

Personal Competence  
Social Competence 
Personal Competences (Social Skills) Students will be able

Autonomy 
Personal Competences (Selfreliance) Students are able in selected areas

Workload in Hours  Depends on choice of courses 
Credit points  6 
Courses 
Information regarding lectures and courses can be found in the corresponding module handbook published separately. 
Module M0736: Linear Algebra 

Courses  

Module Responsible  Prof. Marko Lindner 
Admission Requirements  None 
Recommended Previous Knowledge  None 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 

Skills 

Personal Competence  
Social Competence 
 Students are able to work together (e.g. on their regular home work) in heterogeneously composed teams (i.e., teams from different study programs and background knowledge) and to present their results appropriately (e.g. during exercise class). 
Autonomy 
 Students are capable of checking their understanding of complex
concepts on their own. They can specify open questions precisely and
know where to get help in solving them.

Workload in Hours  Independent Study Time 128, Study Time in Lecture 112 
Credit points  8 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  120 
Assignment for the Following Curricula 
Computer Science: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Core Qualification: Compulsory 
Course L0642: Linear Algebra 
Typ  Lecture 
Hrs/wk  4 
CP  4 
Workload in Hours  Independent Study Time 64, Study Time in Lecture 56 
Lecturer  Dr. Julian Großmann 
Language  EN 
Cycle  WiSe 
Content 
Preliminaries Vector spaces Matrices and linear systems of equations Scalar products and orthogonality Basis transformation Determinants Eigen values 
Literature 
Strang: Linear Algebra Beutelsbacher: Lineare Algebra 
Course L0643: Linear Algebra 
Typ  Recitation Section (large) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Dr. Julian Großmann, Jan Meichsner 
Language  EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L0645: Linear Algebra 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Dr. Julian Großmann 
Language  EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0624: Automata Theory and Formal Languages 

Courses  

Module Responsible  Prof. Tobias Knopp 
Admission Requirements  None 
Recommended Previous Knowledge 
Participating students should be able to  specify algorithms for simple data structures (such as, e.g., arrays) to solve computational problems  apply propositional logic and predicate logic for specifying and understanding mathematical proofs  apply the knowledge and skills taught in the module Discrete Algebraic Structures 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students can explain syntax, semantics, and decision problems of propositional logic, and they are able to give algorithms for solving decision problems. Students can show correspondences to Boolean algebra. Students can describe which application problems are hard to represent with propositional logic, and therefore, the students can motivate predicate logic, and define syntax, semantics, and decision problems for this representation formalism. Students can explain unification and resolution for solving the predicate logic SAT decision problem. Students can also describe syntax, semantics, and decision problems for various kinds of temporal logic, and identify their application areas. The participants of the course can define various kinds of finite automata and can identify relationships to logic and formal grammars. The spectrum that students can explain ranges from deterministic and nondeterministic finite automata and pushdown automata to Turing machines. Students can name those formalism for which nondeterminism is more expressive than determinism. They are also able to demonstrate which decision problems require which expressivity, and, in addition, students can transform decision problems w.r.t. one formalism into decision problems w.r.t. other formalisms. They understand that some formalisms easily induce algorithms whereas others are best suited for specifying systems and their properties. Students can describe the relationships between formalisms such as logic, automata, or grammars. 
Skills 
Students can apply propositional logic as well as predicate logic resolution to a given set of formulas. Students analyze application problems in order to derive propositional logic, predicate logic, or temporal logic formulas to represent them. They can evaluate which formalism is best suited for a particular application problem, and they can demonstrate the application of algorithms for decision problems to specific formulas. Students can also transform nondeterministic automata into deterministic ones, or derive grammars from automata and vice versa. They can show how parsers work, and they can apply algorithms for the language emptiness problem in case of infinite words. 
Personal Competence  
Social Competence  
Autonomy  
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  90 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Core Qualification: Compulsory Orientierungsstudium: Core Qualification: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L0332: Automata Theory and Formal Languages 
Typ  Lecture 
Hrs/wk  2 
CP  4 
Workload in Hours  Independent Study Time 92, Study Time in Lecture 28 
Lecturer  Prof. Tobias Knopp 
Language  EN 
Cycle  SoSe 
Content 

Literature 

Course L0507: Automata Theory and Formal Languages 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. Tobias Knopp 
Language  EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0737: Mathematical Analysis 

Courses  

Module Responsible  Prof. Marko Lindner 
Admission Requirements  None 
Recommended Previous Knowledge  None 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 

Skills 

Personal Competence  
Social Competence 
 Students are able to work together (e.g. on their regular home work) in heterogeneously composed teams (i.e., teams from different study programs and background knowledge) and to present their results appropriately (e.g. during exercise class). 
Autonomy 
 Students are capable of checking their understanding of complex
concepts on their own. They can specify open questions precisely and
know where to get help in solving them.

Workload in Hours  Independent Study Time 128, Study Time in Lecture 112 
Credit points  8 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  120 minutes 
Assignment for the Following Curricula 
Computer Science: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Core Qualification: Compulsory 
Course L0647: Mathematical Analysis 
Typ  Lecture 
Hrs/wk  4 
CP  4 
Workload in Hours  Independent Study Time 64, Study Time in Lecture 56 
Lecturer  Dr. Julian Großmann 
Language  EN 
Cycle  SoSe 
Content 
Convergence, sequences, and series Continuity Elementary functions Differential calculus Integral calculus Sequences of functions 
Literature 
Königsberger: Analysis Forster: Analysis 
Course L0648: Mathematical Analysis 
Typ  Recitation Section (large) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Dr. Julian Großmann, Jan Meichsner 
Language  EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L0649: Mathematical Analysis 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Dr. Julian Großmann 
Language  EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0829: Foundations of Management 

Courses  

Module Responsible  Prof. Christoph Ihl 
Admission Requirements  None 
Recommended Previous Knowledge  Basic Knowledge of Mathematics and Business 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
After taking this module, students know the important basics of many different areas in Business and Management, from Planning and Organisation to Marketing and Innovation, and also to Investment and Controlling. In particular they are able to

Skills 
Students are able to analyse business units with respect to different criteria (organization, objectives, strategies etc.) and to carry out an Entrepreneurship project in a team. In particular, they are able to

Personal Competence  
Social Competence 
Students are able to

Autonomy 
Students are able to

Workload in Hours  Independent Study Time 110, Study Time in Lecture 70 
Credit points  6 
Course achievement  None 
Examination  Subject theoretical and practical work 
Examination duration and scale  several written exams during the semester 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Process Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Naval Architecture: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory Civil and Environmental Engineering: Core Qualification: Compulsory Bioprocess Engineering: Core Qualification: Compulsory Computer Science: Core Qualification: Compulsory Electrical Engineering: Core Qualification: Compulsory Energy and Environmental Engineering: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Naval Architecture: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Logistics and Mobility: Core Qualification: Compulsory Mechanical Engineering: Core Qualification: Compulsory Mechatronics: Core Qualification: Compulsory Orientierungsstudium: Core Qualification: Elective Compulsory Naval Architecture: Core Qualification: Compulsory Technomathematics: Core Qualification: Compulsory Process Engineering: Core Qualification: Compulsory Process Engineering: Core Qualification: Compulsory 
Course L0882: Management Tutorial 
Typ  Recitation Section (large) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Christoph Ihl, Katharina Roedelius, Tobias Vlcek 
Language  DE 
Cycle 
WiSe/ 
Content 
In the management tutorial, the contents of the lecture will be deepened by practical examples and the application of the discussed tools. If there is adequate demand, a problemoriented tutorial will be offered in parallel, which students can choose alternatively. Here, students work in groups on selfselected projects that focus on the elaboration of an innovative business idea from the point of view of an established company or a startup. Again, the business knowledge from the lecture should come to practical use. The group projects are guided by a mentor. 
Literature  Relevante Literatur aus der korrespondierenden Vorlesung. 
Course L0880: Introduction to Management 
Typ  Lecture 
Hrs/wk  3 
CP  3 
Workload in Hours  Independent Study Time 48, Study Time in Lecture 42 
Lecturer  Prof. Christoph Ihl, Prof. Thorsten Blecker, Prof. Christian Lüthje, Prof. Christian Ringle, Prof. Kathrin Fischer, Prof. Cornelius Herstatt, Prof. Wolfgang Kersten, Prof. Matthias Meyer, Prof. Thomas Wrona 
Language  DE 
Cycle 
WiSe/ 
Content 

Literature 
Bamberg, G., Coenenberg, A.: Betriebswirtschaftliche Entscheidungslehre, 14. Aufl., München 2008 Eisenführ, F., Weber, M.: Rationales Entscheiden, 4. Aufl., Berlin et al. 2003 Heinhold, M.: Buchführung in Fallbeispielen, 10. Aufl., Stuttgart 2006. Kruschwitz, L.: Finanzmathematik. 3. Auflage, München 2001. Pellens, B., Fülbier, R. U., Gassen, J., Sellhorn, T.: Internationale Rechnungslegung, 7. Aufl., Stuttgart 2008. Schweitzer, M.: Planung und Steuerung, in: Bea/Friedl/Schweitzer: Allgemeine Betriebswirtschaftslehre, Bd. 2: Führung, 9. Aufl., Stuttgart 2005. Weber, J., Schäffer, U. : Einführung in das Controlling, 12. Auflage, Stuttgart 2008. Weber, J./Weißenberger, B.: Einführung in das Rechnungswesen, 7. Auflage, Stuttgart 2006. 
Module M0553: Objectoriented Programming, Algorithms and Data Structures 

Courses  

Module Responsible  Prof. RolfRainer Grigat 
Admission Requirements  None 
Recommended Previous Knowledge 
This lecture requires proficiency in the German language. For further requirements please refer to the German description. 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students can explain the essentials of software design and the design of a class architecture with reference to existing class libraries and design patterns. Students can describe fundamental data structures of discrete mathematics and assess the complexity of important algorithms for sorting and searching. 
Skills 
Students are able to

Personal Competence  
Social Competence 
Students can work in teams and communicate in forums. 
Autonomy 
Students are able to solve programming tasks such as LZW data compression using SVN Repository and Google Test independently and over a period of two to three weeks. 
Workload in Hours  Independent Study Time 110, Study Time in Lecture 70 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  60 Minutes, Content of Lecture, exercises and material in StudIP 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory Computer Science: Core Qualification: Compulsory Electrical Engineering: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory Orientierungsstudium: Core Qualification: Elective Compulsory 
Course L0131: Objectoriented Programming, Algorithms and Data Structures 
Typ  Lecture 
Hrs/wk  4 
CP  4 
Workload in Hours  Independent Study Time 64, Study Time in Lecture 56 
Lecturer  Prof. RolfRainer Grigat 
Language  DE 
Cycle  SoSe 
Content 
Object oriented analysis and design:
Data structures and algorithmes:

Literature  Skriptum 
Course L0132: Objectoriented Programming, Algorithms and Data Structures 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  2 
Workload in Hours  Independent Study Time 46, Study Time in Lecture 14 
Lecturer  Prof. RolfRainer Grigat 
Language  DE 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0834: Computernetworks and Internet Security 

Courses  

Module Responsible  Prof. Andreas TimmGiel 
Admission Requirements  None 
Recommended Previous Knowledge 
Basics of Computer Science 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students are able to explain important and common Internet protocols in detail and classify them, in order to be able to analyse and develop networked systems in further studies and job. 
Skills 
Students are able to analyse common Internet protocols and evaluate the use of them in different domains. 
Personal Competence  
Social Competence 

Autonomy 
Students can select relevant parts out of high amount of professional knowledge and can independently learn and understand it. 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  120 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Core Qualification: Compulsory Data Science: Core Qualification: Elective Compulsory Electrical Engineering: Core Qualification: Elective Compulsory Engineering Science: Specialisation Mechatronics: Elective Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechatronics: Elective Compulsory Computational Science and Engineering: Core Qualification: Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L1098: Computer Networks and Internet Security 
Typ  Lecture 
Hrs/wk  3 
CP  5 
Workload in Hours  Independent Study Time 108, Study Time in Lecture 42 
Lecturer  Prof. Andreas TimmGiel, Prof. Dieter Gollmann, Dr.Ing. Koojana Kuladinithi 
Language  EN 
Cycle  WiSe 
Content 
In this class an introduction to computer networks with focus on the Internet and its security is given. Basic functionality of complex protocols are introduced. Students learn to understand these and identify common principles. In the exercises these basic principles and an introduction to performance modelling are addressed using computing tasks and (virtual) labs. In the second part of the lecture an introduction to Internet security is given. This class comprises:

Literature 
Further literature is announced at the beginning of the lecture. 
Course L1099: Computer Networks and Internet Security 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Prof. Andreas TimmGiel, Prof. Dieter Gollmann 
Language  EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0953: Introduction to Information Security 

Courses  

Module Responsible  Prof. Dieter Gollmann 
Admission Requirements  None 
Recommended Previous Knowledge  Basics of Computer Science 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students can

Skills 
Students can

Personal Competence  
Social Competence  Students are capable of appreciating the impact of security problems on those affected and of the potential responsibilities for their resolution. 
Autonomy  None 
Workload in Hours  Independent Study Time 110, Study Time in Lecture 70 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  120 minutes 
Assignment for the Following Curricula 
Computer Science: Core Qualification: Compulsory Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory Data Science: Core Qualification: Compulsory Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory 
Course L1114: Introduction to Information Security 
Typ  Lecture 
Hrs/wk  3 
CP  3 
Workload in Hours  Independent Study Time 48, Study Time in Lecture 42 
Lecturer  Prof. Dieter Gollmann 
Language  EN 
Cycle  WiSe 
Content 

Literature 
D. Gollmann: Computer Security, Wiley & Sons, third edition, 2011 Ross Anderson: Security Engineering, Wiley & Sons, second edition, 2008 
Course L1115: Introduction to Information Security 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Dieter Gollmann 
Language  EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0730: Computer Engineering 

Courses  

Module Responsible  Prof. Heiko Falk  
Admission Requirements  None  
Recommended Previous Knowledge 
Basic knowledge in electrical engineering 

Educational Objectives  After taking part successfully, students have reached the following learning results  
Professional Competence  
Knowledge 
This module deals with the foundations of the functionality of computing systems. It covers the layers from the assemblylevel programming down to gates. The module includes the following topics:


Skills 
The students perceive computer systems from the architect's perspective, i.e., they identify the internal structure and the physical composition of computer systems. The students can analyze, how highly specific and individual computers can be built based on a collection of few and simple components. They are able to distinguish between and to explain the different abstraction layers of today's computing systems  from gates and circuits up to complete processors. After successful completion of the module, the students are able to judge the interdependencies between a physical computer system and the software executed on it. In particular, they shall understand the consequences that the execution of software has on the hardwarecentric abstraction layers from the assembly language down to gates. This way, they will be enabled to evaluate the impact that these low abstraction levels have on an entire system's performance and to propose feasible options. 

Personal Competence  
Social Competence 
Students are able to solve similar problems alone or in a group and to present the results accordingly. 

Autonomy 
Students are able to acquire new knowledge from specific literature and to associate this knowledge with other classes. 

Workload in Hours  Independent Study Time 124, Study Time in Lecture 56  
Credit points  6  
Course achievement 


Examination  Written exam  
Examination duration and scale  90 minutes, contents of course and labs  
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Naval Architecture: Compulsory General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Process Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: Compulsory Computer Science: Core Qualification: Compulsory Data Science: Core Qualification: Elective Compulsory Electrical Engineering: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Naval Architecture: Compulsory General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Mechatronics: Core Qualification: Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L0321: Computer Engineering 
Typ  Lecture 
Hrs/wk  3 
CP  4 
Workload in Hours  Independent Study Time 78, Study Time in Lecture 42 
Lecturer  Prof. Heiko Falk 
Language  DE/EN 
Cycle  WiSe 
Content 

Literature 

Course L0324: Computer Engineering 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  2 
Workload in Hours  Independent Study Time 46, Study Time in Lecture 14 
Lecturer  Prof. Heiko Falk 
Language  DE/EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0853: Mathematics III 

Courses  

Module Responsible  Prof. Anusch Taraz 
Admission Requirements  None 
Recommended Previous Knowledge  Mathematics I + II 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 

Skills 

Personal Competence  
Social Competence 

Autonomy 

Workload in Hours  Independent Study Time 128, Study Time in Lecture 112 
Credit points  8 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  60 min (Analysis III) + 60 min (Differential Equations 1) 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Core Qualification: Compulsory Civil and Environmental Engineering: Core Qualification: Compulsory Bioprocess Engineering: Core Qualification: Compulsory Computer Science: Core Qualification: Compulsory Data Science: Core Qualification: Compulsory Digital Mechanical Engineering: Core Qualification: Compulsory Electrical Engineering: Core Qualification: Compulsory Energy and Environmental Engineering: Core Qualification: Compulsory Engineering Science: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Core Qualification: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Mechanical Engineering: Core Qualification: Compulsory Mechatronics: Core Qualification: Compulsory Naval Architecture: Core Qualification: Compulsory Process Engineering: Core Qualification: Compulsory 
Course L1028: Analysis III 
Typ  Lecture 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  WiSe 
Content 
Main features of differential and integrational calculus of several variables

Literature 

Course L1029: Analysis III 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L1030: Analysis III 
Typ  Recitation Section (large) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L1031: Differential Equations 1 (Ordinary Differential Equations) 
Typ  Lecture 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  WiSe 
Content 
Main features of the theory and numerical treatment of ordinary differential equations

Literature 

Course L1032: Differential Equations 1 (Ordinary Differential Equations) 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L1033: Differential Equations 1 (Ordinary Differential Equations) 
Typ  Recitation Section (large) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0562: Computability and Complexity Theory 

Courses  

Module Responsible  Prof. KarlHeinz Zimmermann 
Admission Requirements  None 
Recommended Previous Knowledge  Discrete Algebraic Structures, Automata Theory, Logic, and Formal Language Theory. 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
The students known the important machine models of computability, the class of partial recursive functions, universal computability, Gödel numbering of computations, the theorems of Kleene, Rice, and RiceShapiro, the concept of decidable and undecidable sets, the word problems for semiThue systems, Thue systems, semigroups, and Post correspondence systems, Hilbert's 10th problem, and the basic concepts of complexity theory. 
Skills 
Students are able to investigate the computability of sets and functions and to analyze the complexity of computable functions. 
Personal Competence  
Social Competence 
Students are able to solve specific problems alone or in a group and to present the results accordingly. 
Autonomy 
Students are able to acquire new knowledge from newer literature and to associate the acquired knowledge with other classes. 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  60 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Core Qualification: Compulsory Data Science: Core Qualification: Elective Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L0166: Computability and Complexity Theory 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. KarlHeinz Zimmermann 
Language  DE/EN 
Cycle  SoSe 
Content  
Literature 
Course L0167: Computability and Complexity Theory 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. KarlHeinz Zimmermann 
Language  DE/EN 
Cycle  SoSe 
Content  
Literature 
Module M0732: Software Engineering 

Courses  

Module Responsible  Prof. Sibylle Schupp  
Admission Requirements  None  
Recommended Previous Knowledge 


Educational Objectives  After taking part successfully, students have reached the following learning results  
Professional Competence  
Knowledge 
Students explain the phases of the software life cycle, describe the fundamental terminology and concepts of software engineering, and paraphrase the principles of structured software development. They give examples of softwareengineering tasks of existing largescale systems. They write test cases for different test strategies and devise specifications or models using different notations, and critique both. They explain simple design patterns and the major activities in requirements analysis, maintenance, and project planning. 

Skills 
For a given task in the software life cycle, students identify the corresponding phase and select an appropriate method. They choose the proper approach for quality assurance. They design tests for realistic systems, assess the quality of the tests, and find errors at different levels. They apply and modify nonexecutable artifacts. They integrate components based on interface specifications. 

Personal Competence  
Social Competence 
Students practice peer programming. They explain problems and solutions to their peer. They communicate in English. 

Autonomy 
Using online quizzes and accompanying material for self study, students can assess their level of knowledge continuously and adjust it appropriately. Working on exercise problems, they receive additional feedback. 

Workload in Hours  Independent Study Time 124, Study Time in Lecture 56  
Credit points  6  
Course achievement 


Examination  Written exam  
Examination duration and scale  90 min  
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L0627: Software Engineering 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Sibylle Schupp 
Language  EN 
Cycle  SoSe 
Content 

Literature 
Kassem A. Saleh, Software Engineering, J. Ross Publishing 2009. 
Course L0628: Software Engineering 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Sibylle Schupp 
Language  EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0727: Stochastics 

Courses  

Module Responsible  Prof. Marko Lindner 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge  Students can explain the main definitions of probability, and they can give basic definitions of modeling elements (random variables, events, dependence, independence assumptions) used in discrete and continuous settings (joint and marginal distributions, density functions). Students can describe characteristic notions such as expected values, variance, standard deviation, and moments. Students can define decision problems and explain algorithms for solving these problems (based on the chain rule or Bayesian networks). Algorithms, or estimators as they are caller, can be analyzed in terms of notions such as bias of an estimator, etc. Student can describe the main ideas of stochastic processes and explain algorithms for solving decision and computation problem for stochastic processes. Students can also explain basic statistical detection and estimation techniques. 
Skills 
Students can apply algorithms for solving decision problems, and they can justify whether approximation techniques are good enough in various application contexts, i.e., students can derive estimators and judge whether they are applicable or reliable. 
Personal Competence  
Social Competence 
 Students are able to work together (e.g. on their regular home work) in heterogeneously composed teams (i.e., teams from different study programs and background knowledge) and to present their results appropriately (e.g. during exercise class). 
Autonomy 
 Students are capable of checking their understanding of complex
concepts on their own. They can specify open questions precisely and
know where to get help in solving them.

Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  120 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory Computer Science: Core Qualification: Compulsory Data Science: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory Theoretical Mechanical Engineering: Core Qualification: Elective Compulsory 
Course L0777: Stochastics 
Typ  Lecture 
Hrs/wk  2 
CP  4 
Workload in Hours  Independent Study Time 92, Study Time in Lecture 28 
Lecturer  Dr. Christian Seifert 
Language  DE/EN 
Cycle  SoSe 
Content 
Foundations of probability theory
Practical representations for joint probabilities
Stochastic processes
Detection & estimation

Literature 

Course L0778: Stochastics 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Dr. Christian Seifert 
Language  DE/EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0971: Operating Systems 

Courses  

Module Responsible  Prof. Volker Turau 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students explain the main abstractions process, virtual memory, deadlock, lifelock, and file of operations systems, describe the process states and their transitions, and paraphrase the architectural variants of operating systems. They give examples of existing operating systems and explain their architectures. The participants of the course write concurrent programs using threads, conditional variables and semaphores. Students can describe the variants of realizing a file system. Students explain at least three different scheduling algorithms. 
Skills 
Students are able to use the POSIX libraries for concurrent programming in a correct and efficient way. They are able to judge the efficiency of a scheduling algorithm for a given scheduling task in a given environment. 
Personal Competence  
Social Competence  
Autonomy  
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  90 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Core Qualification: Compulsory Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L1153: Operating Systems 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Volker Turau 
Language  DE 
Cycle  SoSe 
Content 

Literature 

Course L1154: Operating Systems 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Volker Turau 
Language  DE 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0852: Graph Theory and Optimization 

Courses  

Module Responsible  Prof. Anusch Taraz 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 

Skills 

Personal Competence  
Social Competence 

Autonomy 

Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  120 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory Computer Science: Core Qualification: Compulsory Computer Science: Core Qualification: Compulsory Data Science: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory 
Course L1046: Graph Theory and Optimization 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Anusch Taraz 
Language  DE/EN 
Cycle  SoSe 
Content 

Literature 

Course L1047: Graph Theory and Optimization 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Anusch Taraz 
Language  DE/EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0873: Software Industrial Internship 

Courses  

Module Responsible  Prof. KarlHeinz Zimmermann 
Admission Requirements  None 
Recommended Previous Knowledge 
Foundations
of Software Engineering 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students know the important aspects and phases of
software development. 
Skills 
Students can describe the typical phases of software development and are able to contribute to a software project. 
Personal Competence  
Social Competence 
Students are able to specify, implement, and analyze specific basic topics in software development and present them accordingly. 
Autonomy 
Students are able to acquire new knowledge from specific literature and to associate this knowledge with other classes. 
Workload in Hours  Independent Study Time 180, Study Time in Lecture 0 
Credit points  6 
Course achievement  None 
Examination  Written elaboration (accord. to Internship Regulations) 
Examination duration and scale  Die Ausarbeitung wird von der Betreuerin bzw. dem Betreuer der Bachelorarbeit bewertet. 
Assignment for the Following Curricula 
Computer Science: Core Qualification: Compulsory 
Module M0793: Seminars Computer Science and Mathematics 

Courses  

Module Responsible  Prof. KarlHeinz Zimmermann 
Admission Requirements  None 
Recommended Previous Knowledge 
Basic knowledge in Computer Science, Mathematics, and eventually Engineering Science. 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
The students are able to

Skills 
The students are able to

Personal Competence  
Social Competence 
The students are able to

Autonomy 
The students are able to

Workload in Hours  Independent Study Time 96, Study Time in Lecture 84 
Credit points  6 
Course achievement  None 
Examination  Presentation 
Examination duration and scale  Presentation 20 min and discussion 5 min. 
Assignment for the Following Curricula 
Computer Science: Core Qualification: Compulsory 
Course L1781: Seminar Computer Science/Engineering Mathematics 
Typ  Seminar 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. KarlHeinz Zimmermann, Dr. JensPeter Zemke 
Language  DE/EN 
Cycle 
WiSe/ 
Content 

Literature 
Wird vom Seminarveranstalter bekanntgegeben. 
Course L0796: Seminar Computational Engineering Science 
Typ  Seminar 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. KarlHeinz Zimmermann 
Language  DE/EN 
Cycle 
WiSe/ 
Content 

Literature 
Wird vom Seminarveranstalter bekanntgegeben. 
Course L0797: Seminar Computer Science/Mathematics 
Typ  Seminar 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. KarlHeinz Zimmermann, Dr. JensPeter Zemke, Dr. Mehwish Saleemi 
Language  DE/EN 
Cycle 
WiSe/ 
Content 

Literature  Wird vom Seminarveranstalter bekanntgegeben. 
Module M0672: Signals and Systems 

Courses  

Module Responsible  Prof. Gerhard Bauch 
Admission Requirements  None 
Recommended Previous Knowledge 
Mathematics 13 The modul is an introduction to the theory of signals and systems. Good knowledge in maths as covered by the moduls Mathematik 13 is expected. Further experience with spectral transformations (Fourier series, Fourier transform, Laplace transform) is useful but not required. 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge  The students are able to classify and describe signals and linear timeinvariant (LTI) systems using methods of signal and system theory. They are able to apply the fundamental transformations of continuoustime and discretetime signals and systems. They can describe and analyse deterministic signals and systems mathematically in both time and image domain. In particular, they understand the effects in time domain and image domain which are caused by the transition of a continuoustime signal to a discretetime signal. 
Skills  The students are able to describe and analyse deterministic signals and linear timeinvariant systems using methods of signal and system theory. They can analyse and design basic systems regarding important properties such as magnitude and phase response, stability, linearity etc.. They can assess the impact of LTI systems on the signal properties in time and frequency domain. 
Personal Competence  
Social Competence  The students can jointly solve specific problems. 
Autonomy  The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system. 
Workload in Hours  Independent Study Time 110, Study Time in Lecture 70 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  90 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Core Qualification: Compulsory Computer Science: Core Qualification: Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Data Science: Core Qualification: Compulsory Electrical Engineering: Core Qualification: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Mechanical Engineering: Specialisation Mechatronics: Elective Compulsory Mechatronics: Core Qualification: Compulsory Technomathematics: Specialisation III. Engineering Science: Elective Compulsory 
Course L0432: Signals and Systems 
Typ  Lecture 
Hrs/wk  3 
CP  4 
Workload in Hours  Independent Study Time 78, Study Time in Lecture 42 
Lecturer  Prof. Gerhard Bauch 
Language  DE/EN 
Cycle  SoSe 
Content 

Literature 

Course L0433: Signals and Systems 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. Gerhard Bauch 
Language  DE/EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Specialization Computer and Software Engineering
Module M0625: Databases 

Courses  

Module Responsible  Prof. Stefan Schulte 
Admission Requirements  None 
Recommended Previous Knowledge 
Students should have basic knowledge in the following areas:

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
After successful completion of the course, students know:

Skills 
The students acquire the ability to model a database and to work with it. This comprises especially the application of design methodologies and query and definition languages. Furthermore, students are able to apply basic functionalities needed to run a database. 
Personal Competence  
Social Competence 
Students can work on complex problems both independently and in teams. They can exchange ideas with each other and use their individual strengths to solve the problem. 
Autonomy 
Students are able to independently investigate a complex problem and assess which competencies are required to solve it. 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  90 min 
Assignment for the Following Curricula 
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory Data Science: Core Qualification: Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L0337: Databases 
Typ  Lecture 
Hrs/wk  3 
CP  5 
Workload in Hours  Independent Study Time 108, Study Time in Lecture 42 
Lecturer  Prof. Stefan Schulte 
Language  EN 
Cycle  WiSe 
Content 

Literature 

Course L1150: Databases 
Typ  Project/problembased Learning 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Prof. Stefan Schulte 
Language  EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0675: Introduction to Communications and Random Processes 

Courses  

Module Responsible  Prof. Gerhard Bauch 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge  The students know and understand the fundamental building blocks of a communications system. They can describe and analyse the individual building blocks using knowledge of signal and system theory as well as the theory of stochastic processes. The are aware of the essential resources and evaluation criteria of information transmission and are able to design and evaluate a basic communications system. 
Skills  The students are able to design and evaluate a basic communications system. In particular, they can estimate the required resources in terms of bandwidth and power. They are able to assess essential evaluation parameters of a basic communications system such as bandwidth efficiency or bit error rate and to decide for a suitable transmission method. 
Personal Competence  
Social Competence 
The students can jointly solve specific problems. 
Autonomy 
The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system. 
Workload in Hours  Independent Study Time 110, Study Time in Lecture 70 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  90 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Data Science: Core Qualification: Elective Compulsory Electrical Engineering: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Technomathematics: Specialisation III. Engineering Science: Elective Compulsory 
Course L0442: Introduction to Communications and Random Processes 
Typ  Lecture 
Hrs/wk  3 
CP  4 
Workload in Hours  Independent Study Time 78, Study Time in Lecture 42 
Lecturer  Prof. Gerhard Bauch 
Language  DE/EN 
Cycle  WiSe 
Content 

Literature 
K. Kammeyer: Nachrichtenübertragung, Teubner P.A. Höher: Grundlagen der digitalen Informationsübertragung, Teubner. M. Bossert: Einführung in die Nachrichtentechnik, Oldenbourg. J.G. Proakis, M. Salehi: Grundlagen der Kommunikationstechnik. Pearson Studium. J.G. Proakis, M. Salehi: Digital Communications. McGrawHill. S. Haykin: Communication Systems. Wiley J.G. Proakis, M. Salehi: Communication Systems Engineering. PrenticeHall. J.G. Proakis, M. Salehi, G. Bauch, Contemporary Communication Systems. Cengage Learning. 
Course L0443: Introduction to Communications and Random Processes 
Typ  Recitation Section (large) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Prof. Gerhard Bauch 
Language  DE/EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L2354: Introduction to Communications and Random Processes 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Prof. Gerhard Bauch 
Language  DE/EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0941: Combinatorial Structures and Algorithms 

Courses  

Module Responsible  Prof. Anusch Taraz 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 

Skills 

Personal Competence  
Social Competence 

Autonomy 

Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Oral exam 
Examination duration and scale  30 min 
Assignment for the Following Curricula 
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Data Science: Core Qualification: Elective Compulsory Computational Science and Engineering: Specialisation II. Mathematics & Engineering Science: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory 
Course L1100: Combinatorial Structures and Algorithms 
Typ  Lecture 
Hrs/wk  3 
CP  4 
Workload in Hours  Independent Study Time 78, Study Time in Lecture 42 
Lecturer  Prof. Anusch Taraz, Dr. Dennis Clemens 
Language  DE/EN 
Cycle  WiSe 
Content 

Literature 

Course L1101: Combinatorial Structures and Algorithms 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  2 
Workload in Hours  Independent Study Time 46, Study Time in Lecture 14 
Lecturer  Prof. Anusch Taraz 
Language  DE/EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0791: Computer Architecture 

Courses  

Module Responsible  Prof. Heiko Falk  
Admission Requirements  None  
Recommended Previous Knowledge 
Module "Computer Engineering" 

Educational Objectives  After taking part successfully, students have reached the following learning results  
Professional Competence  
Knowledge 
This module presents advanced concepts from the discipline of computer architecture. In the beginning, a broad overview over various programming models is given, both for generalpurpose computers and for specialpurpose machines (e.g., signal processors). Next, foundational aspects of the microarchitecture of processors are covered. Here, the focus particularly lies on the socalled pipelining and the methods used for the acceleration of instruction execution used in this context. The students get to know concepts for dynamic scheduling, branch prediction, superscalar execution of machine instructions and for memory hierarchies. 

Skills 
The students are able to describe the organization of processors. They know the different architectural principles and programming models. The students examine various structures of pipelined processor architectures and are able to explain their concepts and to analyze them w.r.t. criteria like, e.g., performance or energy efficiency. They evaluate different structures of memory hierarchies, know parallel computer architectures and are able to distinguish between instruction and datalevel parallelism. 

Personal Competence  
Social Competence 
Students are able to solve similar problems alone or in a group and to present the results accordingly. 

Autonomy 
Students are able to acquire new knowledge from specific literature and to associate this knowledge with other classes. 

Workload in Hours  Independent Study Time 110, Study Time in Lecture 70  
Credit points  6  
Course achievement 


Examination  Written exam  
Examination duration and scale  90 minutes, contents of course and 4 attestations from the PBL "Computer architecture"  
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory Aircraft Systems Engineering: Core Qualification: Elective Compulsory Aircraft Systems Engineering: Specialisation Avionic Systems: Elective Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory Microelectronics and Microsystems: Specialisation Embedded Systems: Elective Compulsory 
Course L0793: Computer Architecture 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Heiko Falk 
Language  DE/EN 
Cycle  WiSe 
Content 
The theoretical tutorials amplify the lecture's content by solving and discussing exercise sheets and thus serve as exam preparation. Practical aspects of computer architecture are taught in the FPGAbased PBL on computer architecture whose attendance is mandatory. 
Literature 

Course L0794: Computer Architecture 
Typ  Project/problembased Learning 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. Heiko Falk 
Language  DE/EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L1864: Computer Architecture 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Prof. Heiko Falk 
Language  DE/EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0651: Computational Geometry 

Courses  

Module Responsible  Dr. Prashant Batra 
Admission Requirements  None 
Recommended Previous Knowledge 
Linear algebra and analytic geometry as taught in higher secondary school (Computing with vectors a. determinants, Interpretation of scalar product, crossproduct, Representation of lines/planes, Satz d. Pythagoras' theorem, cosine theorem, Thales' theorem, projections/embeddings) Basic data structures (trees, binary trees, search trees, balanced binary trees, linked lists) Definition of a graph 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students can name the basic concepts of computerassisted geometry, describe them with mathematical precision, and explain them by means of examples. Students are conversant with the computational description of geometrical (combinational/topological) facts, including determinant formulas and complexity assessments and proofs for all algorithms, especially outputsensitive algorithms. Students are able to discuss logical connections between these concepts and to explain them by means of examples. 
Skills 
Students can model tasks from computerassisted geometry with the aid of the concepts about which they have learnt and can solve them by means of the methods they have learnt. 
Personal Competence  
Social Competence 
Students are able to discuss with other attendees their own algorithmic suggestions for solving the problems presented. They are also able to work in teams and are conversant with mathematics as a common language. 
Autonomy 
Students are capable of accessing independently further logical connections between the concepts about which they have learnt and are able to verify them. 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  90 min 
Assignment for the Following Curricula 
Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory 
Course L0393: Computational Geoemetry 
Typ  Lecture  
Hrs/wk  2  
CP  4  
Workload in Hours  Independent Study Time 92, Study Time in Lecture 28  
Lecturer  Dr. Prashant Batra  
Language  DE  
Cycle  WiSe  
Content 
Construction of the convex hull of n points, triangulation of a simple polygon
Construction of Delaunaytriangulation and Voronoidiagram Algorithms and data structures for the construction of arrangements, and HamSandwichCuts. the intersection of halfplanes, the optimization of a linear functional over the latter. Efficiente determination of all intersection of (orthogonal) lines (line segments) Approximative computation of the diameter of a point set Randomised incremental algorithms Basics of lattice point theory , LLLalgorithm and application in integervalued optimization. Basics of motion planning 

Literature 
Computational Geometry Algorithms and Applications Authors:
Springer eBook: http://dx.doi.org/10.1007/9783540779742
Springer eBook: http://dx.doi.org/10.1007/354027619X O’Rourke, Joseph ISBN: 0521440343 ; 0521445922
Devadoss, Satyan L.; O’Rourke, Joseph

Course L0394: Computational Geoemetry 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Dr. Prashant Batra 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0972: Distributed Systems 

Courses  

Module Responsible  Prof. Volker Turau 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students explain the main abstractions of Distributed Systems (Marshalling, proxy, service, address, Remote procedure call, synchron/asynchron system). They describe the pros and cons of different types of interprocess communication. They give examples of existing middleware solutions. The participants of the course know the main architectural variants of distributed systems, including their pros and cons. Students can describe at least three different synchronization mechanisms. 
Skills 
Students can realize distributed systems using at least three different techniques:

Personal Competence  
Social Competence  
Autonomy  
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  120 min 
Assignment for the Following Curricula 
Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L1155: Distributed Systems 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Volker Turau 
Language  DE 
Cycle  WiSe 
Content 

Literature 

Course L1156: Distributed Systems 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Volker Turau 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M1242: Quantum Mechanics for Engineers 

Courses  

Module Responsible  Prof. Wolfgang Hansen  
Admission Requirements  None  
Recommended Previous Knowledge 


Educational Objectives  After taking part successfully, students have reached the following learning results  
Professional Competence  
Knowledge  The students are able to describe and explain basic terms and principles of quantum mechanics. They can distinguish commons and differences to classical physics and know, in which situations quantum mechanical phenomena may be expected.  
Skills  The students get the ability to apply concepts and methods of quantum mechanics to simple problems and systems. Vice versa, they are also able to comprehend requirements and principles of quantum mechanical devices.  
Personal Competence  
Social Competence  The students discuss contents of the lectures and present solutions to simple quantum mechanical problems in small groups during the exercises.  
Autonomy  The students are able to independently find answers to simple questions on quantum mechanical systems. The students are able to independently comprehend literature to more complex subjects with quantum mechanical background.  
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56  
Credit points  6  
Course achievement 


Examination  Oral exam  
Examination duration and scale  90 Minuten  
Assignment for the Following Curricula 
Computer Science: Specialisation Computational Mathematics: Elective Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Core Qualification: Elective Compulsory 
Course L1686: Quantum Mechanics for Engineers 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Wolfgang Hansen 
Language  DE 
Cycle  WiSe 
Content 
This lecture introduces into fundamental concepts, methods, and definitions in quantum mechanics, which are needed in modern material and device science. Applications will be discussed using examples in the field of electronic and optical devices. Central topics are: Schrödinger equation, wave function, operators, eigenstates, eigenvalues, quantum wells, harmonic oscillator, tunnel processes, resonant tunnel diode, band structure, density of states, quantum statistics, Zenerdiode, stationary perturbation calculation with the quantumconfined Stark effect as an example, Fermi’s golden rule and transition matrix elements, heterostructure laser, quantum cascade laser, manyparticle physics, molecules and exchange interaction, quantum bits and quantum cryptography. 
Literature 

Course L1688: Quantum Mechanics for Engineers 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Wolfgang Hansen 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0754: Compiler Construction 

Courses  

Module Responsible  Prof. Sibylle Schupp 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students explain the workings of a compiler and break down a compilation task in different phases. They apply and modify the major algorithms for compiler construction and code improvement. They can rewrite those algorithms in a programming language, run and test them. They choose appropriate internal languages and representations and justify their choice. They explain and modify implementations of existing compiler frameworks and experiment with frameworks and tools. 
Skills 
Students design and implement arbitrary compilation phases. They integrate their code in existing compiler frameworks. They organize their compiler code properly as a software project. They generalize algorithms for compiler construction to algorithms that analyze or synthesize software. 
Personal Competence  
Social Competence 
Students develop the software in a team. They explain problems and solutions to their team members. They present and defend their software in class. They communicate in English. 
Autonomy 
Students develop their software independently and define milestones by themselves. They receive feedback throughout the entire project. They organize the software project so that they can assess their progress themselves. 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Subject theoretical and practical work 
Examination duration and scale  Software (Compiler) 
Assignment for the Following Curricula 
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L0703: Compiler Construction 
Typ  Lecture 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. Sibylle Schupp 
Language  EN 
Cycle  SoSe 
Content 

Literature 
Alfred Aho, Jeffrey Ullman, Ravi Sethi, and Monica S. Lam, Compilers: Principles, Techniques, and Tools, 2nd edition Aarne Ranta, Implementing Programming Languages, An Introduction to Compilers and Interpreters, with an appendix coauthored by Markus Forsberg, College Publications, London, 2012 
Course L0704: Compiler Construction 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  4 
Workload in Hours  Independent Study Time 92, Study Time in Lecture 28 
Lecturer  Prof. Sibylle Schupp 
Language  EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0634: Introduction into Medical Technology and Systems 

Courses  

Module Responsible  Prof. Alexander Schlaefer  
Admission Requirements  None  
Recommended Previous Knowledge 
principles of math (algebra, analysis/calculus) 

Educational Objectives  After taking part successfully, students have reached the following learning results  
Professional Competence  
Knowledge 
The students can explain principles of medical technology, including imaging systems, computer aided surgery, and medical information systems. They are able to give an overview of regulatory affairs and standards in medical technology. 

Skills 
The students are able to evaluate systems and medical devices in the context of clinical applications. 

Personal Competence  
Social Competence 
The students describe a problem in medical technology as a project, and define tasks that are solved in a joint effort. 

Autonomy 
The students can reflect their knowledge and document the results of their work. They can present the results in an appropriate manner. 

Workload in Hours  Independent Study Time 110, Study Time in Lecture 70  
Credit points  6  
Course achievement 


Examination  Written exam  
Examination duration and scale  90 minutes  
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Data Science: Core Qualification: Elective Compulsory Electrical Engineering: Core Qualification: Elective Compulsory Engineering Science: Specialisation Biomedical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory Computational Science and Engineering: Specialisation II. Mathematics & Engineering Science: Elective Compulsory Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory Biomedical Engineering: Specialisation Implants and Endoprostheses: Elective Compulsory Biomedical Engineering: Specialisation Medical Technology and Control Theory: Elective Compulsory Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory Technomathematics: Specialisation III. Engineering Science: Elective Compulsory 
Course L0342: Introduction into Medical Technology and Systems 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Alexander Schlaefer 
Language  DE 
Cycle  SoSe 
Content 
 imaging systems 
Literature 
Wird in der Veranstaltung bekannt gegeben. 
Course L0343: Introduction into Medical Technology and Systems 
Typ  Project Seminar 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. Alexander Schlaefer 
Language  DE 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L1876: Introduction into Medical Technology and Systems 
Typ  Recitation Section (large) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Prof. Alexander Schlaefer 
Language  DE 
Cycle  SoSe 
Content 
 imaging systems 
Literature 
Wird in der Veranstaltung bekannt gegeben. 
Module M1300: Software Development 

Courses  

Module Responsible  Prof. Sibylle Schupp 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students explain the fundamental concepts of agile methods, describe the process of 
Skills 
For a given task on a legacy system, students identify the corresponding parts in the system and select an appropriate method for understanding the details. They choose the proper approach of splitting a task in independent testable and extensible pieces and, thus, solve the task with proper methods for quality assurance. They design tests for legacy systems, create automated builds, and find errors at different levels. They integrate the resulting artifacts in a continuous development environment 
Personal Competence  
Social Competence 
Students discuss different design decisions in a group. They defend their solutions orally. They communicate in English. 
Autonomy 
Using accompanying tools, students can assess their level of knowledge continuously and adjust it appropriately. Within limits, they can set their own learning goals. Upon successful completion, students can identify and formulate concrete problems of software systems and propose solutions. Within this field, they can conduct independent studies to acquire the necessary competencies. They can devise plans to arrive at new solutions or assess existing ones. 
Workload in Hours  Independent Study Time 138, Study Time in Lecture 42 
Credit points  6 
Course achievement  None 
Examination  Subject theoretical and practical work 
Examination duration and scale  Software 
Assignment for the Following Curricula 
Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory 
Course L1790: Software Development 
Typ  Project/problembased Learning 
Hrs/wk  2 
CP  5 
Workload in Hours  Independent Study Time 122, Study Time in Lecture 28 
Lecturer  Prof. Sibylle Schupp 
Language  EN 
Cycle  SoSe 
Content 

Literature 
Duvall, Paul M. Continuous Integration. Pearson Education India, 2007. Martin, Robert Cecil. Agile software development: principles, patterns, and practices. Prentice Hall PTR, 2003. http://scrumkompakt.de/ Myers, Glenford J., Corey Sandler, and Tom Badgett. The art of software testing. John Wiley & Sons, 2011. 
Course L1789: Software Development 
Typ  Lecture 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Prof. Sibylle Schupp 
Language  EN 
Cycle  SoSe 
Content 

Literature 
Duvall, Paul M. Continuous Integration. Pearson Education India, 2007. Martin, Robert Cecil. Agile software development: principles, patterns, and practices. Prentice Hall PTR, 2003. http://scrumkompakt.de/ Myers, Glenford J., Corey Sandler, and Tom Badgett. The art of software testing. John Wiley & Sons, 2011. 
Module M0803: Embedded Systems 

Courses  

Module Responsible  Prof. Heiko Falk  
Admission Requirements  None  
Recommended Previous Knowledge  Computer Engineering  
Educational Objectives  After taking part successfully, students have reached the following learning results  
Professional Competence  
Knowledge 
Embedded systems can be defined as information processing systems embedded into enclosing products. This course teaches the foundations of such systems. In particular, it deals with an introduction into these systems (notions, common characteristics) and their specification languages (models of computation, hierarchical automata, specification of distributed systems, task graphs, specification of realtime applications, translations between different models). Another part covers the hardware of embedded systems: Sonsors, A/D and D/A converters, realtime capable communication hardware, embedded processors, memories, energy dissipation, reconfigurable logic and actuators. The course also features an introduction into realtime operating systems, middleware and realtime scheduling. Finally, the implementation of embedded systems using hardware/software codesign (hardware/software partitioning, highlevel transformations of specifications, energyefficient realizations, compilers for embedded processors) is covered. 

Skills 
After having attended the course, students shall be able to realize simple embedded systems. The students shall realize which relevant parts of technological competences to use in order to obtain a functional embedded systems. In particular, they shall be able to compare different models of computations and feasible techniques for systemlevel design. They shall be able to judge in which areas of embedded system design specific risks exist. 

Personal Competence  
Social Competence 
Students are able to solve similar problems alone or in a group and to present the results accordingly. 

Autonomy 
Students are able to acquire new knowledge from specific literature and to associate this knowledge with other classes. 

Workload in Hours  Independent Study Time 124, Study Time in Lecture 56  
Credit points  6  
Course achievement 


Examination  Written exam  
Examination duration and scale  90 minutes, contents of course and labs  
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory Electrical Engineering: Core Qualification: Elective Compulsory Engineering Science: Specialisation Mechatronics: Elective Compulsory Aircraft Systems Engineering: Core Qualification: Elective Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechatronics: Elective Compulsory Computational Science and Engineering: Core Qualification: Compulsory Mechatronics: Specialisation System Design: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Mechatronics: Core Qualification: Elective Compulsory Microelectronics and Microsystems: Specialisation Embedded Systems: Elective Compulsory 
Course L0805: Embedded Systems 
Typ  Lecture 
Hrs/wk  3 
CP  4 
Workload in Hours  Independent Study Time 78, Study Time in Lecture 42 
Lecturer  Prof. Heiko Falk 
Language  EN 
Cycle  SoSe 
Content 

Literature 

Course L0806: Embedded Systems 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  2 
Workload in Hours  Independent Study Time 46, Study Time in Lecture 14 
Lecturer  Prof. Heiko Falk 
Language  EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M1269: Lab CyberPhysical Systems 

Courses  

Module Responsible  Prof. Heiko Falk 
Admission Requirements  None 
Recommended Previous Knowledge  Module "Embedded Systems" 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
CyberPhysical Systems (CPS) are tightly integrated with their surrounding environment, via sensors, A/D and D/A converters, and actors. Due to their particular application areas, highly specialized sensors, processors and actors are common. Accordingly, there is a large variety of different specification approaches for CPS  in contrast to classical software engineering approaches. Based on practical experiments using robot kits and computers, the basics of specification and modelling of CPS are taught. The lab introduces into the area (basic notions, characteristical properties) and their specification techniques (models of computation, hierarchical automata, data flow models, petri nets, imperative approaches). Since CPS frequently perform control tasks, the lab's experiments will base on simple control applications. The experiments will use stateoftheart industrial specification tools (MATLAB/Simulink, LabVIEW, NXC) in order to model cyberphysical models that interact with the environment via sensors and actors. 
Skills  After successful attendance of the lab, students are able to develop simple CPS. They understand the interdependencies between a CPS and its surrounding processes which stem from the fact that a CPS interacts with the environment via sensors, A/D converters, digital processors, D/A converters and actors. The lab enables students to compare modelling approaches, to evaluate their advantages and limitations, and to decide which technique to use for a concrete task. They will be able to apply these techniques to practical problems. They obtain first experiences in hardwarerelated software development, in industryrelevant specification tools and in the area of simple control applications. 
Personal Competence  
Social Competence 
Students are able to solve similar problems alone or in a group and to present the results accordingly. 
Autonomy 
Students are able to acquire new knowledge from specific literature and to associate this knowledge with other classes. 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written elaboration 
Examination duration and scale  Execution and documentation of all lab experiments 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation II. Mathematics & Engineering Science: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Mechatronics: Specialisation System Design: Elective Compulsory Mechatronics: Technical Complementary Course: Elective Compulsory 
Course L1740: Lab CyberPhysical Systems 
Typ  Project/problembased Learning 
Hrs/wk  4 
CP  6 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Lecturer  Prof. Heiko Falk 
Language  DE/EN 
Cycle  SoSe 
Content 

Literature 

Specialization Computational Mathematics
Module M0675: Introduction to Communications and Random Processes 

Courses  

Module Responsible  Prof. Gerhard Bauch 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge  The students know and understand the fundamental building blocks of a communications system. They can describe and analyse the individual building blocks using knowledge of signal and system theory as well as the theory of stochastic processes. The are aware of the essential resources and evaluation criteria of information transmission and are able to design and evaluate a basic communications system. 
Skills  The students are able to design and evaluate a basic communications system. In particular, they can estimate the required resources in terms of bandwidth and power. They are able to assess essential evaluation parameters of a basic communications system such as bandwidth efficiency or bit error rate and to decide for a suitable transmission method. 
Personal Competence  
Social Competence 
The students can jointly solve specific problems. 
Autonomy 
The students are able to acquire relevant information from appropriate literature sources. They can control their level of knowledge during the lecture period by solving tutorial problems, software tools, clicker system. 
Workload in Hours  Independent Study Time 110, Study Time in Lecture 70 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  90 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Data Science: Core Qualification: Elective Compulsory Electrical Engineering: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Technomathematics: Specialisation III. Engineering Science: Elective Compulsory 
Course L0442: Introduction to Communications and Random Processes 
Typ  Lecture 
Hrs/wk  3 
CP  4 
Workload in Hours  Independent Study Time 78, Study Time in Lecture 42 
Lecturer  Prof. Gerhard Bauch 
Language  DE/EN 
Cycle  WiSe 
Content 

Literature 
K. Kammeyer: Nachrichtenübertragung, Teubner P.A. Höher: Grundlagen der digitalen Informationsübertragung, Teubner. M. Bossert: Einführung in die Nachrichtentechnik, Oldenbourg. J.G. Proakis, M. Salehi: Grundlagen der Kommunikationstechnik. Pearson Studium. J.G. Proakis, M. Salehi: Digital Communications. McGrawHill. S. Haykin: Communication Systems. Wiley J.G. Proakis, M. Salehi: Communication Systems Engineering. PrenticeHall. J.G. Proakis, M. Salehi, G. Bauch, Contemporary Communication Systems. Cengage Learning. 
Course L0443: Introduction to Communications and Random Processes 
Typ  Recitation Section (large) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Prof. Gerhard Bauch 
Language  DE/EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L2354: Introduction to Communications and Random Processes 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Prof. Gerhard Bauch 
Language  DE/EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0833: Introduction to Control Systems 

Courses  

Module Responsible  Prof. Herbert Werner 
Admission Requirements  None 
Recommended Previous Knowledge 
Representation of signals and systems in time and frequency domain, Laplace transform 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 

Skills 

Personal Competence  
Social Competence  Students can work in small groups to jointly solve technical problems, and experimentally validate their controller designs 
Autonomy 
Students can obtain information from provided sources (lecture notes, software documentation, experiment guides) and use it when solving given problems. They can assess their knowledge in weekly online tests and thereby control their learning progress. 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  120 min 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Core Qualification: Compulsory Bioprocess Engineering: Core Qualification: Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Data Science: Core Qualification: Elective Compulsory Electrical Engineering: Core Qualification: Compulsory Energy and Environmental Engineering: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Product Development and Production: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Naval Architecture: Compulsory General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory Green Technologies: Energy, Water, Climate: Core Qualification: Compulsory Computational Science and Engineering: Core Qualification: Compulsory Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory Logistics and Mobility: Specialisation Information Technology: Elective Compulsory Logistics and Mobility: Specialisation Traffic Planning and Systems: Elective Compulsory Logistics and Mobility: Specialisation Production Management and Processes: Elective Compulsory Mechanical Engineering: Core Qualification: Compulsory Mechatronics: Core Qualification: Compulsory Technomathematics: Specialisation III. Engineering Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course Core Studies: Elective Compulsory Process Engineering: Core Qualification: Compulsory Engineering and Management  Major in Logistics and Mobility: Specialisation Information Technology: Elective Compulsory Engineering and Management  Major in Logistics and Mobility: Specialisation Traffic Planning and Systems: Elective Compulsory Engineering and Management  Major in Logistics and Mobility: Specialisation Production Management and Processes: Elective Compulsory 
Course L0654: Introduction to Control Systems 
Typ  Lecture 
Hrs/wk  2 
CP  4 
Workload in Hours  Independent Study Time 92, Study Time in Lecture 28 
Lecturer  Prof. Herbert Werner 
Language  DE 
Cycle  WiSe 
Content 
Signals and systems
Feedback systems
Root locus techniques
Frequency response techniques
Time delay systems
Digital control
Software tools

Literature 

Course L0655: Introduction to Control Systems 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Prof. Herbert Werner 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0941: Combinatorial Structures and Algorithms 

Courses  

Module Responsible  Prof. Anusch Taraz 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 

Skills 

Personal Competence  
Social Competence 

Autonomy 

Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Oral exam 
Examination duration and scale  30 min 
Assignment for the Following Curricula 
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Data Science: Core Qualification: Elective Compulsory Computational Science and Engineering: Specialisation II. Mathematics & Engineering Science: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory 
Course L1100: Combinatorial Structures and Algorithms 
Typ  Lecture 
Hrs/wk  3 
CP  4 
Workload in Hours  Independent Study Time 78, Study Time in Lecture 42 
Lecturer  Prof. Anusch Taraz, Dr. Dennis Clemens 
Language  DE/EN 
Cycle  WiSe 
Content 

Literature 

Course L1101: Combinatorial Structures and Algorithms 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  2 
Workload in Hours  Independent Study Time 46, Study Time in Lecture 14 
Lecturer  Prof. Anusch Taraz 
Language  DE/EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0662: Numerical Mathematics I 

Courses  

Module Responsible  Prof. Sabine Le Borne 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students are able to

Skills 
Students are able to

Personal Competence  
Social Competence 
Students are able to

Autonomy 
Students are capable

Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  90 minutes 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Aircraft Systems Engineering: Elective Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Elective Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Energy Systems: Elective Compulsory Bioprocess Engineering: Specialisation A  General Bioprocess Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Data Science: Core Qualification: Compulsory Electrical Engineering: Core Qualification: Elective Compulsory Engineering Science: Core Qualification: Compulsory Engineering Science: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Elective Compulsory Computational Science and Engineering: Core Qualification: Compulsory Mechanical Engineering: Specialisation Theoretical Mechanical Engineering: Compulsory Mechanical Engineering: Specialisation Energy Systems: Elective Compulsory Mechanical Engineering: Specialisation Mechatronics: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course Core Studies: Elective Compulsory Process Engineering: Specialisation Process Engineering: Elective Compulsory 
Course L0417: Numerical Mathematics I 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Sabine Le Borne 
Language  EN 
Cycle  WiSe 
Content 

Literature 

Course L0418: Numerical Mathematics I 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Sabine Le Borne, Dr. JensPeter Zemke 
Language  EN 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M1242: Quantum Mechanics for Engineers 

Courses  

Module Responsible  Prof. Wolfgang Hansen  
Admission Requirements  None  
Recommended Previous Knowledge 


Educational Objectives  After taking part successfully, students have reached the following learning results  
Professional Competence  
Knowledge  The students are able to describe and explain basic terms and principles of quantum mechanics. They can distinguish commons and differences to classical physics and know, in which situations quantum mechanical phenomena may be expected.  
Skills  The students get the ability to apply concepts and methods of quantum mechanics to simple problems and systems. Vice versa, they are also able to comprehend requirements and principles of quantum mechanical devices.  
Personal Competence  
Social Competence  The students discuss contents of the lectures and present solutions to simple quantum mechanical problems in small groups during the exercises.  
Autonomy  The students are able to independently find answers to simple questions on quantum mechanical systems. The students are able to independently comprehend literature to more complex subjects with quantum mechanical background.  
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56  
Credit points  6  
Course achievement 


Examination  Oral exam  
Examination duration and scale  90 Minuten  
Assignment for the Following Curricula 
Computer Science: Specialisation Computational Mathematics: Elective Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Core Qualification: Elective Compulsory 
Course L1686: Quantum Mechanics for Engineers 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Wolfgang Hansen 
Language  DE 
Cycle  WiSe 
Content 
This lecture introduces into fundamental concepts, methods, and definitions in quantum mechanics, which are needed in modern material and device science. Applications will be discussed using examples in the field of electronic and optical devices. Central topics are: Schrödinger equation, wave function, operators, eigenstates, eigenvalues, quantum wells, harmonic oscillator, tunnel processes, resonant tunnel diode, band structure, density of states, quantum statistics, Zenerdiode, stationary perturbation calculation with the quantumconfined Stark effect as an example, Fermi’s golden rule and transition matrix elements, heterostructure laser, quantum cascade laser, manyparticle physics, molecules and exchange interaction, quantum bits and quantum cryptography. 
Literature 

Course L1688: Quantum Mechanics for Engineers 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Wolfgang Hansen 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0651: Computational Geometry 

Courses  

Module Responsible  Dr. Prashant Batra 
Admission Requirements  None 
Recommended Previous Knowledge 
Linear algebra and analytic geometry as taught in higher secondary school (Computing with vectors a. determinants, Interpretation of scalar product, crossproduct, Representation of lines/planes, Satz d. Pythagoras' theorem, cosine theorem, Thales' theorem, projections/embeddings) Basic data structures (trees, binary trees, search trees, balanced binary trees, linked lists) Definition of a graph 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students can name the basic concepts of computerassisted geometry, describe them with mathematical precision, and explain them by means of examples. Students are conversant with the computational description of geometrical (combinational/topological) facts, including determinant formulas and complexity assessments and proofs for all algorithms, especially outputsensitive algorithms. Students are able to discuss logical connections between these concepts and to explain them by means of examples. 
Skills 
Students can model tasks from computerassisted geometry with the aid of the concepts about which they have learnt and can solve them by means of the methods they have learnt. 
Personal Competence  
Social Competence 
Students are able to discuss with other attendees their own algorithmic suggestions for solving the problems presented. They are also able to work in teams and are conversant with mathematics as a common language. 
Autonomy 
Students are capable of accessing independently further logical connections between the concepts about which they have learnt and are able to verify them. 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  90 min 
Assignment for the Following Curricula 
Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory 
Course L0393: Computational Geoemetry 
Typ  Lecture  
Hrs/wk  2  
CP  4  
Workload in Hours  Independent Study Time 92, Study Time in Lecture 28  
Lecturer  Dr. Prashant Batra  
Language  DE  
Cycle  WiSe  
Content 
Construction of the convex hull of n points, triangulation of a simple polygon
Construction of Delaunaytriangulation and Voronoidiagram Algorithms and data structures for the construction of arrangements, and HamSandwichCuts. the intersection of halfplanes, the optimization of a linear functional over the latter. Efficiente determination of all intersection of (orthogonal) lines (line segments) Approximative computation of the diameter of a point set Randomised incremental algorithms Basics of lattice point theory , LLLalgorithm and application in integervalued optimization. Basics of motion planning 

Literature 
Computational Geometry Algorithms and Applications Authors:
Springer eBook: http://dx.doi.org/10.1007/9783540779742
Springer eBook: http://dx.doi.org/10.1007/354027619X O’Rourke, Joseph ISBN: 0521440343 ; 0521445922
Devadoss, Satyan L.; O’Rourke, Joseph

Course L0394: Computational Geoemetry 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Dr. Prashant Batra 
Language  DE 
Cycle  WiSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0668: Algebra and Control 

Courses  

Module Responsible  Dr. Prashant Batra 
Admission Requirements  None 
Recommended Previous Knowledge 
Basics of Real Analysis and Linear Algebra of Vector Spaces and either of: Introduction to Control Theory or: Discrete Mathematics 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students can

Skills 
Students are able to

Personal Competence  
Social Competence  After completing the module, students are able to solve subjectrelated tasks and to present the results. 
Autonomy  Students are provided with tasks which are examrelated so that they can examine their learning progress and reflect on it. 
Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Oral exam 
Examination duration and scale  30 min 
Assignment for the Following Curricula 
Computer Science: Specialisation Computational Mathematics: Elective Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory 
Course L0428: Algebra and Control 
Typ  Lecture 
Hrs/wk  2 
CP  4 
Workload in Hours  Independent Study Time 92, Study Time in Lecture 28 
Lecturer  Dr. Prashant Batra 
Language  DE/EN 
Cycle  SoSe 
Content 
 Algebraic control methods, polynomial and fractional approach
 Parametrization of all stabilizing controllers  Selected methods of pole assignment.  Filtering and sensitivity minimization  Euclidean algorithm, diophantine equations over rings  SmithMcMillan normal form 
Literature 

Course L0429: Algebra and Control 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  2 
Workload in Hours  Independent Study Time 32, Study Time in Lecture 28 
Lecturer  Dr. Prashant Batra 
Language  DE/EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0715: Solvers for Sparse Linear Systems 

Courses  

Module Responsible  Prof. Sabine Le Borne 
Admission Requirements  None 
Recommended Previous Knowledge 

Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 
Students can

Skills 
Students are able to

Personal Competence  
Social Competence 
Students are able to

Autonomy 
Students are capable

Workload in Hours  Independent Study Time 124, Study Time in Lecture 56 
Credit points  6 
Course achievement  None 
Examination  Oral exam 
Examination duration and scale  20 min 
Assignment for the Following Curricula 
Computer Science: Specialisation Computational Mathematics: Elective Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Computer Science: Specialisation II. Mathematics and Engineering Science: Elective Compulsory Data Science: Core Qualification: Elective Compulsory Computational Science and Engineering: Specialisation II. Mathematics & Engineering Science: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory 
Course L0583: Solvers for Sparse Linear Systems 
Typ  Lecture 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Sabine Le Borne 
Language  EN 
Cycle  SoSe 
Content 

Literature 

Course L0584: Solvers for Sparse Linear Systems 
Typ  Recitation Section (small) 
Hrs/wk  2 
CP  3 
Workload in Hours  Independent Study Time 62, Study Time in Lecture 28 
Lecturer  Prof. Sabine Le Borne 
Language  EN 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Module M0854: Mathematics IV 

Courses  

Module Responsible  Prof. Anusch Taraz 
Admission Requirements  None 
Recommended Previous Knowledge  Mathematics 1  III 
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 

Skills 

Personal Competence  
Social Competence 

Autonomy 

Workload in Hours  Independent Study Time 68, Study Time in Lecture 112 
Credit points  6 
Course achievement  None 
Examination  Written exam 
Examination duration and scale  60 min (Complex Functions) + 60 min (Differential Equations 2) 
Assignment for the Following Curricula 
General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory General Engineering Science (German program, 7 semester): Specialisation Naval Architecture: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Electrical Engineering: Core Qualification: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory Computational Science and Engineering: Specialisation II. Mathematics & Engineering Science: Elective Compulsory Mechanical Engineering: Specialisation Mechatronics: Compulsory Mechanical Engineering: Specialisation Theoretical Mechanical Engineering: Elective Compulsory Mechatronics: Core Qualification: Compulsory Naval Architecture: Core Qualification: Compulsory Theoretical Mechanical Engineering: Technical Complementary Course Core Studies: Elective Compulsory 
Course L1043: Differential Equations 2 (Partial Differential Equations) 
Typ  Lecture 
Hrs/wk  2 
CP  1 
Workload in Hours  Independent Study Time 2, Study Time in Lecture 28 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  SoSe 
Content 
Main features of the theory and numerical treatment of partial differential equations

Literature 

Course L1044: Differential Equations 2 (Partial Differential Equations) 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L1045: Differential Equations 2 (Partial Differential Equations) 
Typ  Recitation Section (large) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L1038: Complex Functions 
Typ  Lecture 
Hrs/wk  2 
CP  1 
Workload in Hours  Independent Study Time 2, Study Time in Lecture 28 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  SoSe 
Content 
Main features of complex analysis

Literature 

Course L1041: Complex Functions 
Typ  Recitation Section (small) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Course L1042: Complex Functions 
Typ  Recitation Section (large) 
Hrs/wk  1 
CP  1 
Workload in Hours  Independent Study Time 16, Study Time in Lecture 14 
Lecturer  Dozenten des Fachbereiches Mathematik der UHH 
Language  DE 
Cycle  SoSe 
Content  See interlocking course 
Literature  See interlocking course 
Thesis
Module M001: Bachelor Thesis 

Courses  

Module Responsible  Professoren der TUHH 
Admission Requirements 

Recommended Previous Knowledge  
Educational Objectives  After taking part successfully, students have reached the following learning results 
Professional Competence  
Knowledge 

Skills 

Personal Competence  
Social Competence 

Autonomy 

Workload in Hours  Independent Study Time 360, Study Time in Lecture 0 
Credit points  12 
Course achievement  None 
Examination  Thesis 
Examination duration and scale  According to General Regulations 
Assignment for the Following Curricula 
General Engineering Science (German program): Thesis: Compulsory General Engineering Science (German program, 7 semester): Thesis: Compulsory Civil and Environmental Engineering: Thesis: Compulsory Bioprocess Engineering: Thesis: Compulsory Computer Science: Thesis: Compulsory Data Science: Thesis: Compulsory Digital Mechanical Engineering: Thesis: Compulsory Electrical Engineering: Thesis: Compulsory Energy and Environmental Engineering: Thesis: Compulsory Engineering Science: Thesis: Compulsory General Engineering Science (English program): Thesis: Compulsory General Engineering Science (English program, 7 semester): Thesis: Compulsory Green Technologies: Energy, Water, Climate: Thesis: Compulsory Computational Science and Engineering: Thesis: Compulsory Logistics and Mobility: Thesis: Compulsory Mechanical Engineering: Thesis: Compulsory Mechatronics: Thesis: Compulsory Naval Architecture: Thesis: Compulsory Technomathematics: Thesis: Compulsory Teilstudiengang Lehramt ElektrotechnikInformationstechnik: Thesis: Compulsory Teilstudiengang Lehramt Metalltechnik: Thesis: Compulsory Process Engineering: Thesis: Compulsory Engineering and Management  Major in Logistics and Mobility: Thesis: Compulsory 