Module Manual
Bachelor
Computer Science
Cohort: Winter Term 2017
Updated: 28th June 2017
Content
Module M0561: Discrete Algebraic Structures |
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Courses | ||||||||||||
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Module Responsible | Prof. Karl-Heinz 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 |
Examination | Written exam |
Examination duration and scale | 120 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory Computer Science: Core qualification: Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory Computational Science and Engineering: Core qualification: 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. Karl-Heinz 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. Karl-Heinz Zimmermann |
Language | DE |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0575: Procedural Programming |
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Courses | ||||||||||||||||
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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:
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Skills |
|
Personal Competence | |
Social Competence |
The students acquire the following skills:
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Autonomy |
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Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
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 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 | Laboratory 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 Complementary 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 Non-technical
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. Self-reliance, self-management, 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 cross-disciplinarily 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 start-ups in a goal-oriented way. The fields of teaching are augmented by soft skills offers and a foreign language offer. Here, the focus is on encouraging goal-oriented 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
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Skills |
Professional Competence (Skills) In selected sub-areas students can
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Personal Competence | |
Social Competence |
Personal Competences (Social Skills) Students will be able
|
Autonomy |
Personal Competences (Self-reliance) Students are able in selected areas
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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 M0731: Functional Programming |
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Courses | ||||||||||||||||
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Module Responsible | Prof. Sibylle Schupp |
Admission Requirements | None |
Recommended Previous Knowledge | Discrete mathematics at high-school 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 read-eval-print 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 natural-language 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 |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Core qualification: Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation 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 |
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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 |
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Literature |
Graham Hutton, Programming in Haskell, Cambridge University Press 2007. |
Module M0736: Linear Algebra |
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Courses | ||||||||||||||||
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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 |
Examination | Written exam |
Examination duration and scale | 120 |
Assignment for the Following Curricula |
Computer Science: Core qualification: Compulsory General Engineering Science (English program): 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. Francisco Javier Hoecker-Escuti |
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. Francisco Javier Hoecker-Escuti |
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. Francisco Javier Hoecker-Escuti |
Language | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0553: Objectoriented Programming, Algorithms and Data Structures |
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Courses | ||||||||||||
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Module Responsible | Prof. Rolf-Rainer Grigat |
Admission Requirements |
None |
Recommended Previous Knowledge |
Lecture Prozedurale Programmierung or equivalent proficiency in imperative programming Mandatory prerequisite for this lecture is proficiency in imperative programming (C, Pascal, Fortran or similar). You should be familiar with simple data types (integer, double, char), arrays, if-then-else, for, while, procedure calls or function calls, pointers, and you should have used all those in your own programs and therefore should be proficient with editor, compiler, linker and debugger. In this lecture we will immediately start with the introduction of objects and we will not repeat the basics mentioned above. This remark is especially important for AIW, GES, LUM because those prerequisites are not part of the curriculum. They are prerequisites for the start of those curricula in general. The programs ET, CI and IIW include those prerequisites in the first semester in the lecture Prozedurale Programmierung. . |
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
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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 |
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): Specialisation Computer Science: Compulsory 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): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory Computational Science and Engineering: Core qualification: Compulsory Logistics and Mobility: Specialisation Engineering Science: Elective Compulsory Technomathematics: Core qualification: 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. Rolf-Rainer 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. Rolf-Rainer Grigat |
Language | DE |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0624: Automata Theory and Formal Languages |
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Courses | ||||||||||||
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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 |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Core qualification: Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Core qualification: 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 |
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Literature |
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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 M0732: Software Engineering |
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Courses | ||||||||||||
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Module Responsible | Prof. Sibylle Schupp |
Admission Requirements |
None |
Recommended Previous Knowledge |
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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 software-engineering tasks of existing large-scale 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 non-executable 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 on-line 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 |
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 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 M0737: Mathematical Analysis |
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Courses | ||||||||||||||||
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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 |
Examination | Written exam |
Examination duration and scale | 120 minutes |
Assignment for the Following Curricula |
Computer Science: Core qualification: Compulsory General Engineering Science (English program): 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. Francisco Javier Hoecker-Escuti |
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. Francisco Javier Hoecker-Escuti |
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. Francisco Javier Hoecker-Escuti |
Language | EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0829: Foundations of Management |
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Courses | ||||||||||||
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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 |
Examination | Written exam |
Examination duration and scale | 90 minutes |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program): Specialisation Process Engineering: Compulsory General Engineering Science (German program): Specialisation Bioprocess Engineering: Compulsory General Engineering Science (German program): Specialisation Energy and Enviromental Engineering: Compulsory General Engineering Science (German program): Specialisation Civil- and Enviromental Engeneering: Compulsory General Engineering Science (German program): Specialisation Mechanical Engineering: Compulsory General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory General Engineering Science (German program): Specialisation Naval Architecture: Compulsory 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): Specialisation Civil- and Enviromental Engeneering: Compulsory General Engineering Science (English program): Specialisation Bioprocess Engineering: Compulsory General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program): Specialisation Energy and Enviromental Engineering: Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program): Specialisation Mechanical Engineering: Compulsory General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory General Engineering Science (English program): Specialisation Naval Architecture: Compulsory General Engineering Science (English program): Specialisation Process Engineering: 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 Naval Architecture: Core qualification: Compulsory Technomathematics: Core qualification: Compulsory Process Engineering: Core qualification: Compulsory |
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. |
Course L0882: Project Entrepreneurship |
Typ | Problem-based Learning |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Christoph Ihl, Ann-Isabell Hnida, Hamed Farhadian, Katharina Roedelius, Oliver Welling, Maximilian Muelke |
Language | DE |
Cycle |
WiSe/ |
Content |
In this project module, students work on an Entrepreneurship project. They are required to go through all relevant steps, from the first idea to the concept, using their knowledge from the corresponding lecture. Project work is carried out in teams with the support of a mentor. |
Literature | Relevante Literatur aus der korrespondierenden Vorlesung. |
Module M0730: Computer Engineering |
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Courses | ||||||||||||
|
Module Responsible | Prof. Heiko Falk |
Admission Requirements | None |
Recommended Previous Knowledge |
Basic knowledge in electrical engineering The successful completion of the labs will be honored during the evaluation of the module's examination according to the following rules:
|
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 assembly-level 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 hardware-centric 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 |
Examination | Written exam |
Examination duration and scale | 90 minutes, contents of course and labs |
Assignment for the Following Curricula |
General Engineering Science (German program): Core qualification: 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 Naval Architecture: Compulsory General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: 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 Computer Science: Core qualification: Compulsory Electrical Engineering: Core qualification: Compulsory General Engineering Science (English program): Core qualification: 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 Naval Architecture: Compulsory General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Process 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 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 |
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 |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0834: Computernetworks and Internet Security |
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Courses | ||||||||||||
|
Module Responsible | Prof. Andreas Timm-Giel |
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 |
Examination | Written exam |
Examination duration and scale | 120 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Core qualification: Compulsory Electrical Engineering: Core qualification: Elective Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Core qualification: Compulsory Technomathematics: Specialisation II. Informatics: Elective 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 Timm-Giel, Prof. Dieter Gollmann |
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 Timm-Giel, Prof. Dieter Gollmann |
Language | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0953: Introduction to Information Security |
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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 |
Examination | Written exam |
Examination duration and scale | 120 minutes |
Assignment for the Following Curricula |
Computer Science: Core qualification: Compulsory Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: 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. Chris Brzuska, 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 M0853: Mathematics III |
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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 |
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): Core qualification: Compulsory 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 Electrical Engineering: Core qualification: Compulsory Energy and Environmental Engineering: Core qualification: Compulsory General Engineering Science (English program): 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 |
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Courses | ||||||||||||
|
Module Responsible | Prof. Karl-Heinz 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 Rice-Shapiro, the concept of decidable and undecidable sets, the word problems for semi-Thue systems, Thue systems, semi-groups, and Post correspondence systems, Hilbert's 10-th 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 |
Examination | Oral exam |
Examination duration and scale | 20 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 Computer Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory Technomathematics: Core qualification: 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. Karl-Heinz 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. Karl-Heinz Zimmermann |
Language | DE/EN |
Cycle | SoSe |
Content | |
Literature |
Module M0672: Signals and Systems |
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Courses | ||||||||||||
|
Module Responsible | Prof. Gerhard Bauch |
Admission Requirements |
None |
Recommended Previous Knowledge |
Mathematics 1-3 The modul is an introduction to the theory of signals and systems. Good knowledge in maths as covered by the moduls Mathematik 1-3 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 time-invariant (LTI) systems using methods of signal and system theory. They are able to apply the fundamental transformations of continuous-time and discrete-time 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 continuous-time signal to a discrete-time signal. |
Skills | The students are able to describe and analyse deterministic signals and linear time-invariant 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 124, Study Time in Lecture 56 |
Credit points | 6 |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program): Specialisation Process Engineering: Compulsory General Engineering Science (German program): Specialisation Bioprocess Engineering: Compulsory General Engineering Science (German program): Specialisation Civil- and Enviromental Engeneering: Compulsory General Engineering Science (German program): Specialisation Mechanical Engineering: Compulsory General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Process Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Bioprocess Engineering: 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 Energy Systems: 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 Mechatronics: Compulsory General Engineering Science (German program, 7 semester): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory Computer Science: Core qualification: Compulsory Electrical Engineering: Core qualification: Compulsory General Engineering Science (English program): Specialisation Civil- and Enviromental Engeneering: Compulsory General Engineering Science (English program): Specialisation Bioprocess Engineering: Compulsory General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program): Specialisation Mechanical Engineering: Compulsory General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory General Engineering Science (English program): Specialisation Process Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Process Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Bioprocess Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: 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 Theoretical Mechanical Engineering: Compulsory Computational Science and Engineering: Core qualification: 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 (large) |
Hrs/wk | 1 |
CP | 2 |
Workload in Hours | Independent Study Time 46, Study Time in Lecture 14 |
Lecturer | Prof. Gerhard Bauch |
Language | DE/EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0727: Stochastics |
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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 |
Examination | Written exam |
Examination duration and scale | 120 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory Computer Science: Core qualification: Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory Computational Science and Engineering: Core qualification: Compulsory Logistics and Mobility: Specialisation Engineering Science: 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. Francisco Javier Hoecker-Escuti |
Language | 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. Francisco Javier Hoecker-Escuti |
Language | EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0852: Graph Theory and Optimization |
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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 |
Examination | Written exam |
Examination duration and scale | 120 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory Computer Science: Core qualification: Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory Computational Science and Engineering: Core qualification: 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 |
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 |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0971: Operating Systems |
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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 |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Core qualification: Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation 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 M0793: Seminars Computer Science and Mathematics |
||||||||||||||||
Courses | ||||||||||||||||
|
Module Responsible | Prof. Karl-Heinz 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 know who to acquire basic knowledge in a rudimentary field of Computer Science, Mathematics, or Engineering Science. |
Skills | The students are able to elaborate self-reliantly a rudimentary subfield of Computer Science, Mathematics, or Engineering Science. |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Independent Study Time 96, Study Time in Lecture 84 |
Credit points | 6 |
Examination | Presentation |
Examination duration and scale | Pro Seminar erfolgt der Scheinerwerb durch Präsentation (Seminarvortrag 25 min und Diskussion 5 min) |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Compulsory Computer Science: Core qualification: Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Compulsory Computational Science and Engineering: Core qualification: Compulsory |
Course L0797: Seminar Computational Mathematics/Computer Science |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Prof. Karl-Heinz Zimmermann, Dr. Jens-Peter 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. Karl-Heinz Zimmermann |
Language | DE/EN |
Cycle |
WiSe/ |
Content |
|
Literature |
Wird vom Seminarveranstalter bekanntgegeben. |
Course L1781: Seminar Engineering Mathematics/Computer Science |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Prof. Karl-Heinz Zimmermann, Dr. Jens-Peter Zemke |
Language | DE/EN |
Cycle |
WiSe/ |
Content |
|
Literature |
Wird vom Seminarveranstalter bekanntgegeben. |
Module M0873: Software Industrial Internship |
||||
Courses | ||||
|
Module Responsible | Prof. Karl-Heinz 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 |
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 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 on-line tests and thereby control their learning progress. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Examination | Written exam |
Examination duration and scale | 120 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Core qualification: 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 Naval Architecture: Compulsory General Engineering Science (German program, 7 semester): Specialisation Civil Engineering: 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 Bioprocess Engineering: Core qualification: Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Electrical Engineering: Core qualification: Compulsory Energy and Environmental Engineering: Core qualification: Compulsory General Engineering Science (English program): Core qualification: 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 Naval Architecture: Compulsory General Engineering Science (English program, 7 semester): Specialisation Civil Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Energy and Enviromental Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Process 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: Specialisation Engineering Science: Elective Compulsory Mechanical Engineering: Core qualification: Compulsory Mechatronics: Core qualification: Compulsory Technomathematics: Specialisation III. Engineering Science: Elective Compulsory Technomathematics: Specialisation III. Engineering Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course Core Studies: Elective Compulsory Process Engineering: Core qualification: 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 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, cross-product, 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 computer-assisted 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 output-sensitive 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 computer-assisted 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 |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computational Mathematics: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: 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 Delaunay-triangulation and Voronoi-diagram Algorithms and data structures for the construction of arrangements, and Ham-Sandwich-Cuts. the intersection of half-planes, 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 , LLL-algorithm and application in integer-valued optimization. Basics of motion planning |
||||||||||||||||||||||||
Literature |
Computational Geometry Algorithms and Applications Authors:
Springer e-Book: http://dx.doi.org/10.1007/978-3-540-77974-2
Springer e-Book: http://dx.doi.org/10.1007/3-540-27619-X O’Rourke, Joseph ISBN: 0-521-44034-3 ; 0-521-44592-2
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 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 |
Examination | Written exam |
Examination duration and scale | 90 minutes |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Computer Science: Compulsory General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory 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 Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Electrical Engineering: Core qualification: Elective Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Materials in Engineering Sciences: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: 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 Biomedical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Mechanical Engineering, Focus Biomechanics: Compulsory Computational Science and Engineering: Core qualification: 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, Dr. Patricio Farrell |
Language | DE/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. Patricio Farrell |
Language | DE/EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0863: Numerics and Computer Algebra |
||||||||||||||||
Courses | ||||||||||||||||
|
Module Responsible | Prof. Siegfried Rump |
Admission Requirements | none |
Recommended Previous Knowledge |
Basic knowledge in numerics and discrete mathematics |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
The students know the difference between precision and accuracy. For several basic problems they know how to solve them approximatively and exactly. They can distinguish between efficiently, not efficiently and principally unsolvable problems. |
Skills |
The students are able to analyze complex problems in mathematics and computer science. In particular they can analyze the sensitivity of the solution. For several problems they can derive best possible algorithms with respect to the accuracy of the computed result. |
Personal Competence | |
Social Competence |
The students have the skills to solve problems together in small groups and to present the achieved results in an appropriate manner. |
Autonomy |
The students are able to retrieve necessary informations from the given literature and to combine them with the topics of the lecture. Throughout the lecture they can check their abilities and knowledge on the basis of given exercises and test questions providing an aid to optimize their learning process. |
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 |
Credit points | 6 |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computational Mathematics: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory Technomathematics: Core qualification: Elective Compulsory |
Course L0115: Numerical Mathematics and Computer Algebra |
Typ | Lecture |
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 |
· Basic Linear Algebra Subroutines (BLAS)
|
Literature |
Higham, N.J.: Accuracy and stability of numerical algorithms, SIAM Publications, Philadelphia, 2nd edition, 2002 Golub, G.H. and Van Loan, Ch.: Matrix Computations, John Hopkins University Press, 3rd edition, 1996 Knuth, D.E.: The Art of Computer Programming: Seminumerical Algorithms, Vol. 2. Addison Wesley, Reading, Massachusetts, 1969 |
Course L1060: Numerics and Computer Algebra |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Prof. Siegfried Rump |
Language | DE |
Cycle | WiSe |
Content | Seminar accompanying the lectures (q.v. lecture contents) |
Literature |
Higham, N.J.: Accuracy and stability of numerical algorithms, SIAM Publications, Philadelphia, 2nd edition, 2002 Golub, G.H. and Van Loan, Ch.: Matrix Computations, John Hopkins University Press, 3rd edition, 1996 Knuth, D.E.: The Art of Computer Programming: Seminumerical Algorithms, Vol. 2. Addison Wesley, Reading, Massachusetts, 1969 |
Course L0117: Numerical Mathematics and Computer Algebra |
Typ | Recitation Section (small) |
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 |
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 |
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 Computational Science and Engineering: Specialisation Computer 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 |
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 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 |
Examination | Written exam |
Examination duration and scale | 90 minutes |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Electrical Engineering: Core qualification: Elective Compulsory Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: 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, Zener-diode, stationary perturbation calculation with the quantum-confined Stark effect as an example, Fermi’s golden rule and transition matrix elements, heterostructure laser, quantum cascade laser, many-particle 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 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 | |
Autonomy | |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computational Mathematics: Elective Compulsory Electrical Engineering: Core qualification: Elective Compulsory Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory Technomathematics: Core qualification: 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 - Smith-McMillan 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 M1062: Mathematical Statistics |
||||||||||||
Courses | ||||||||||||
|
Module Responsible | Prof. Anusch Taraz |
Admission Requirements | none |
Recommended Previous Knowledge |
Mathematical Stochastics Measure Theory and Stochastics |
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 |
Examination | Written exam |
Examination duration and scale | 120 minutes |
Assignment for the Following Curricula |
General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory |
Course L1339: Mathematical Statistics |
Typ | Lecture |
Hrs/wk | 3 |
CP | 4 |
Workload in Hours | Independent Study Time 78, Study Time in Lecture 42 |
Lecturer | Dozenten des Fachbereiches Mathematik der UHH |
Language | DE/EN |
Cycle | SoSe |
Content |
|
Literature |
|
Course L1340: Mathematical Statistics |
Typ | Recitation Section (small) |
Hrs/wk | 1 |
CP | 2 |
Workload in Hours | Independent Study Time 46, Study Time in Lecture 14 |
Lecturer | Dozenten des Fachbereiches Mathematik der UHH |
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 |
Examination | Oral exam |
Examination duration and scale | 20 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computational Mathematics: Elective Compulsory Electrical Engineering: Core qualification: Elective Compulsory Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory Computational Science and Engineering: Specialisation Computer 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 | DE/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 | DE/EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1061: Measure Theory and Stochastics |
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Courses | ||||||||||||
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Module Responsible | Prof. Anusch Taraz |
Admission Requirements | none |
Recommended Previous Knowledge |
Mathematical Stochastics |
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 |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computational Mathematics: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory |
Course L1335: Measure Theory and Stochastics |
Typ | Lecture |
Hrs/wk | 3 |
CP | 4 |
Workload in Hours | Independent Study Time 78, Study Time in Lecture 42 |
Lecturer | Dozenten des Fachbereiches Mathematik der UHH |
Language | DE/EN |
Cycle | SoSe |
Content |
|
Literature |
|
Course L1338: Measure Theory and Stochastics |
Typ | Recitation Section (small) |
Hrs/wk | 1 |
CP | 2 |
Workload in Hours | Independent Study Time 46, Study Time in Lecture 14 |
Lecturer | Dozenten des Fachbereiches Mathematik der UHH |
Language | DE/EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0854: Mathematics IV |
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Courses | ||||||||||||||||||||||||||||
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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 |
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): Specialisation Electrical Engineering: Compulsory General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory General Engineering Science (German program): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory General Engineering Science (German program): Specialisation Naval Architecture: Compulsory 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 Mechanical Engineering, Focus Theoretical Mechanical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Naval Architecture: Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Electrical Engineering: Core qualification: Compulsory General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program): Specialisation Naval Architecture: Compulsory General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Mechatronics: Compulsory General Engineering Science (English program): Specialisation Mechanical Engineering, Focus Theoretical Mechanical Engineering: 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 General Engineering Science (English program, 7 semester): Specialisation Naval Architecture: Compulsory Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory Mechanical Engineering: Specialisation Theoretical Mechanical Engineering: Compulsory Mechanical Engineering: Specialisation Mechatronics: 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 |
Module M0675: Introduction to Communications and Random Processes |
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Courses | ||||||||||||
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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 124, Study Time in Lecture 56 |
Credit points | 6 |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Core qualification: Compulsory General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Compulsory Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory Technomathematics: Specialisation III. Engineering Science: Elective Compulsory Technomathematics: Core qualification: 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. McGraw-Hill. S. Haykin: Communication Systems. Wiley J.G. Proakis, M. Salehi: Communication Systems Engineering. Prentice-Hall. 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 | 2 |
Workload in Hours | Independent Study Time 46, Study Time in Lecture 14 |
Lecturer | Prof. Gerhard Bauch |
Language | DE/EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0783: Measurements: Methods and Data Processing |
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Courses | ||||||||||||||||
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Module Responsible | Prof. Alexander Schlaefer |
Admission Requirements |
none |
Recommended Previous Knowledge |
principles of mathematics |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
The students are able to explain the purpose of metrology and the acquisition and processing of measurements. They can detail aspects of probability theory and errors, and explain the processing of stochastic signals. Students know methods to digitalize and describe measured signals. |
Skills |
The students are able to evaluate problems of metrology and to apply methods for describing and processing of measurements. |
Personal Competence | |
Social Competence |
The students solve problems in small groups. |
Autonomy |
The students can reflect their knowledge and discuss and evaluate their results. |
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 |
Credit points | 6 |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Electrical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Electrical Engineering: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Core qualification: Compulsory General Engineering Science (English program): Specialisation Electrical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Electrical Engineering: Elective Compulsory Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory Technomathematics: Specialisation III. Engineering Science: Elective Compulsory Technomathematics: Core qualification: Elective Compulsory |
Course L0781: EE Experimental Lab |
Typ | Laboratory Course |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Prof. Alexander Schlaefer, Prof. Christian Schuster, Prof. Günter Ackermann, Prof. Rolf-Rainer Grigat, Prof. Arne Jacob, Prof. Herbert Werner, Dozenten des SD E, Prof. Heiko Falk |
Language | DE |
Cycle | WiSe |
Content | lab experiments: digital circuits, semiconductors, micro controllers, analog circuits, AC power, electrical machines |
Literature | Wird in der Lehrveranstaltung festgelegt |
Course L0779: Measurements: Methods and Data Processing |
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 | WiSe |
Content |
introduction, systems and errors in metrology, probability theory, measuring stochastic signals, describing measurements, acquisition of analog signals, applied metrology |
Literature |
Puente León, Kiencke: Messtechnik, Springer 2012 |
Course L0780: Measurements: Methods and Data Processing |
Typ | Recitation Section (small) |
Hrs/wk | 1 |
CP | 1 |
Workload in Hours | Independent Study Time 16, Study Time in Lecture 14 |
Lecturer | Prof. Alexander Schlaefer |
Language | DE |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0972: Distributed Systems |
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Courses | ||||||||||||
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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 |
Examination | Written exam |
Examination duration and scale | 120 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation 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 |
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Courses | ||||||||||||
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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 |
Examination | Written exam |
Examination duration and scale | 90 minutes |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computational Mathematics: Elective Compulsory Electrical Engineering: Core qualification: Elective Compulsory Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: 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, Zener-diode, stationary perturbation calculation with the quantum-confined Stark effect as an example, Fermi’s golden rule and transition matrix elements, heterostructure laser, quantum cascade laser, many-particle 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 M0625: Databases |
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Courses | ||||||||||||
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Module Responsible | NN |
Admission Requirements | None |
Recommended Previous Knowledge |
Students should habe basic knowledge in the following areas:
|
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students can explain the general architecture of an application system that is based on a database. They describe the syntax and semantics of the Entity Relationship conceptual modeling languages, and they can enumerate basic decision problems and know which features of a domain model can be captured with ER and which features cannot be represented. Furthermore, students can summarize the features of the relational data model, and can describe how ER models can be systematically transformed into the relational data model. Student are able to discuss dependency theory using the operators of relational algebra, and they know how to use relational algebra as a query language. In addition, they can sketch the main modules of the architecture of a database system from an implementation point of view. Storage and index structures as well as query answering and optimization techniques can be explained. The role of transactions can be described in terms of ACID conditions and common recovery mechanisms can be characterized. The students can recall why recursion is important for query languages and describe how Datalog can be used and implemented.They demonstrate how Datalog can be used for information integration. For solving ER decision problems the students can explain description logics with their syntax and semantics, they describe description logic decision problems and explain how these problems can be mapped onto each other. They can sketch the idea of ontology-based data access and can name the main complexity measure in database theory. Last but not least, the students can describe the main features of XML and can explain XPath and XQuery as query languages. |
Skills |
Students can apply ER for describing domains for which they receive a textual description, and students can transform relational schemata with a given set of functional dependencies into third normal form or even Boyce-Codd normal form. They can also apply relational algebra, SQL, or Datalog to specify queries. Using specific datasets, they can explain how index structures work (e.g., B-trees) and how index structures change while data is added or deleted. They can rewrite queries for better performance of query evaluation. Students can analyse which query language expressivity is required for which application problem. Description logics can be applied for domain modeling, and students can transform ER diagrams into description logics in order to check for consistency and implicit subsumption relations. They solve data integration problems using Datalog and LAV or GAV rules. Students can apply XPath and Xquery to retrieve certain patterns in XML data. |
Personal Competence | |
Social Competence | Students develop an understanding of social structures in a company used for developing real-world products. They know the responsibilities of data analysts, programmers, and managers in the overall production process. |
Autonomy | |
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 |
Credit points | 6 |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory Technomathematics: Core qualification: Elective Compulsory |
Course L0337: Databases |
Typ | Lecture |
Hrs/wk | 4 |
CP | 5 |
Workload in Hours | Independent Study Time 94, Study Time in Lecture 56 |
Lecturer | NN |
Language | EN |
Cycle | WiSe |
Content |
|
Literature |
|
Course L1150: Databases |
Typ | Problem-based Learning |
Hrs/wk | 1 |
CP | 1 |
Workload in Hours | Independent Study Time 16, Study Time in Lecture 14 |
Lecturer | NN |
Language | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0791: Computer Architecture |
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Courses | ||||||||||||||||
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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 general-purpose computers and for special-purpose machines (e.g., signal processors). Next, foundational aspects of the micro-architecture of processors are covered. Here, the focus particularly lies on the so-called 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 data-level 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 |
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): Specialisation Computer Science: Compulsory General Engineering Science (German program, 7 semester): Specialisation Computer Science: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory General Engineering Science (English program): Specialisation Computer Science: Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: 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 FPGA-based PBL on computer architecture whose attendance is mandatory. |
Literature |
|
Course L0794: Computer Architecture |
Typ | Problem-based 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 M0941: Combinatorial Structures and Algorithms |
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Courses | ||||||||||||
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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 |
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 Computational Science and Engineering: Specialisation Computer 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 |
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 M0803: Embedded Systems |
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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 real-time applications, translations between different models). Another part covers the hardware of embedded systems: Sonsors, A/D and D/A converters, real-time capable communication hardware, embedded processors, memories, energy dissipation, reconfigurable logic and actuators. The course also features an introduction into real-time operating systems, middleware and real-time scheduling. Finally, the implementation of embedded systems using hardware/software co-design (hardware/software partitioning, high-level transformations of specifications, energy-efficient 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 system-level 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 |
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: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Core qualification: Elective Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Core qualification: Compulsory Mechatronics: Specialisation System Design: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: 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 M0754: Compiler Construction |
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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 re-write 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 |
Examination | Project |
Examination duration and scale | Software (Compiler) |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation 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 M0758: Application Security |
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Courses | ||||||||||||
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Module Responsible | Prof. Dieter Gollmann |
Admission Requirements | None |
Recommended Previous Knowledge | Familiarity with Information security, fundamentals of cryptography, Web protocols and the architecture of the Web |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students can name current approaches for securing selected applications, in particular of web applications |
Skills |
Students are capable of
|
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 | Students are capable of acquiring knowledge independently from professional publications, technical standards, and other sources, and are capable of applying newly acquired knowledge to new problems. |
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 |
Credit points | 6 |
Examination | Written exam |
Examination duration and scale | 120 minutes |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation Information and Communication Technology: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems: Elective Compulsory International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory Technomathematics: Specialisation II. Informatics: Elective Compulsory Technomathematics: Core qualification: Elective Compulsory |
Course L0726: Application 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 | SoSe |
Content |
|
Literature |
Webseiten der OMG, W3C, OASIS, WS-Security, OECD, TCG D. Gollmann: Computer Security, 3rd edition, Wiley (2011) R. Anderson: Security Engineering, 2nd edition, Wiley (2008) U. Lang: CORBA Security, Artech House, 2002 |
Course L0729: Application 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 | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1269: Lab Cyber-Physical Systems |
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Courses | ||||||||
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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 |
Cyber-Physical 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 state-of-the-art industrial specification tools (MATLAB/Simulink, LabVIEW, NXC) in order to model cyber-physical 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 hardware-related software development, in industry-relevant 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 |
Examination | Project |
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 Computer and Software Engineering: Elective Compulsory General Engineering Science (English program, 7 semester): Specialisation Computer Science: Elective Compulsory Computational Science and Engineering: Specialisation Computer 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 Cyber-Physical Systems |
Typ | Problem-based 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 |
|
Module M1300: Software Development |
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Courses | ||||||||||||
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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 |
Examination | Project |
Examination duration and scale | Software |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation Computer Science: Elective Compulsory |
Course L1790: Software Development |
Typ | Problem-based 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://scrum-kompakt.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://scrum-kompakt.de/ Myers, Glenford J., Corey Sandler, and Tom Badgett. The art of software testing. John Wiley & Sons, 2011. |
Module M0634: Introduction into Medical Technology and Systems |
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Courses | ||||||||||||||||
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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 |
Examination | Written exam |
Examination duration and scale | 90 minutes |
Assignment for the Following Curricula |
General Engineering Science (German program): Specialisation Biomedical Engineering: Compulsory General Engineering Science (German program, 7 semester): Specialisation Biomedical Engineering: Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Core qualification: Elective Compulsory General Engineering Science (English program): Specialisation Biomedical Engineering: Compulsory General Engineering Science (English program, 7 semester): Specialisation Biomedical Engineering: Compulsory Computational Science and Engineering: Specialisation Engineering Sciences: Elective Compulsory Computational Science and Engineering: Specialisation Computer 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 | |
Literature |
Module M-001: Bachelor Thesis |
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Courses | ||||
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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 |
Examination | according to Subject Specific Regulations |
Examination duration and scale | laut FSPO |
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 Electrical Engineering: Thesis: Compulsory Energy and Environmental Engineering: Thesis: Compulsory General Engineering Science (English program): Thesis: Compulsory General Engineering Science (English program, 7 semester): 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 xx: Thesis: Compulsory Process Engineering: Thesis: Compulsory |