Program description
Content
Core Qualification
Module M0523: Business & Management |
Module Responsible | Prof. Matthias Meyer |
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 |
|
Autonomy |
|
Workload in Hours | Depends on choice of courses |
Credit points | 6 |
Course L1486: Business Model Generation & Green Technologies |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 0 |
Lecturer | Prof. Michael Prange |
Language | EN |
Cycle | WiSe |
Content |
Based on examples and case studies primarily in the field of green technologies, students learn the basics of |
Literature |
Präsentationsfolien, Beispiele und Fallstudien aus der Vorlesung Presentation slides, examples and case studies from the lecture |
Course L1487: Corporate Entrepreneurship & Green Innovation |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | |
Lecturer | Prof. Michael Prange |
Language | EN |
Cycle | WiSe |
Content |
Based on examples and case studies primarily in the field of green innovation, students learn the basics of |
Literature |
Präsentationsfolien, Beispiele und Fallstudien aus der Vorlesung Presentation slides, examples and case studies from the lecture |
Course L1280: Creation of Business Opportunities |
Typ | Project-/problem-based Learning |
Hrs/wk | 3 |
CP | 4 |
Workload in Hours | Independent Study Time 78, Study Time in Lecture 42 |
Examination Form | Referat |
Examination duration and scale | 30 Minuten |
Lecturer | Prof. Christoph Ihl |
Language | EN |
Cycle | SoSe |
Content |
Important note: This course is part of an 6 ECTS module
consisting of two courses "Entrepreneurship” & “Creation of Business
Opportunities”, which have to be taken together in one semester. Startups are temporary, team-based organizations, which can form both
within and outside of established companies, to pursue one central
objective: taking a new venture idea to market by designing a business
model that can be scaled to a full-grown company. In this
course, students will form startup teams around self-selected ideas and
run through the process just like real startups would do in the first
three months of intensive work. Startup Engineering takes an incremental
and iterative approach, in that it favors variety and alternatives over
one detailed, linear five-year business plan to reach steady state
operations. From a problem solving and systems thinking perspective,
student teams create different possible versions of a new venture and
alternative hypotheses about value creation for customers and value
capture vis-à-vis competitors. We will draw on recent scientific findings about international success factors of new venture design. To test critical hypotheses early on,
student teams engage in scientific, evidence-based, experimental trial-and-error
learning process that measures real progress. |
Literature |
• Blank, S. & Dorf, B. (2012). The startup owner's manual. |
Course L2348: Drivers of success for projects |
Typ | Project-/problem-based Learning |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Schriftliche Ausarbeitung |
Examination duration and scale | 0 |
Lecturer | Lucia Pohl |
Language | DE |
Cycle |
WiSe/ |
Content | |
Literature |
Course L1384: Intellectual Property |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | |
Lecturer | Janna Thomsen, Cathérine Elkemann |
Language | DE |
Cycle | WiSe |
Content |
|
Literature |
Quellen und Materialen wird im Internet zur Verfügung gestellt |
Course L2347: Human resource management for engineers |
Typ | Project-/problem-based Learning |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Schriftliche Ausarbeitung |
Examination duration and scale | 0 |
Lecturer | Helge Kochskämper |
Language | DE |
Cycle | WiSe |
Content | |
Literature |
Course L1711: Innovation Debates |
Typ | Project-/problem-based Learning |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Fachtheoretisch-fachpraktische Arbeit |
Examination duration and scale | 3 Präsentationen der schriftlichen Ausarbeitung à 20 Minutes |
Lecturer | Prof. Daniel Heiner Ehls |
Language | EN |
Cycle | WiSe |
Content |
Scientific knowledge grows continuously but also experiences certain alignments over time. For example, early cultures had the believe of a flat earth while latest research has a spherical earth model. Also in social science and business management, from time to time certain concepts that have even been the predominant paradigm are challenged by new observations and models. Consequently, certain controversies emerge and build the base for advancing theory and managerial practice. With this lecture, we put ourselves in the middle of heated debates for informed academics and practitioners of the day after tomorrow. The lecture targets several controversies in the domain of technology strategy and innovation management. By the classical academic method and the novel problem based learning format of a structured discussion, a given controversy is scrutinized. On selected topics, students will discuss a dispute and gain a thorough understanding. Specifically, based on a brief introduction of a motion, a affirmative constructive as well as a negative constructive is presented by two different student groups. Each presentation is followed by a response of the other group and questions from the class. Topics range from latest theories and concepts for value capture, to the importance of operating within a global marketplace, to cutting edge approaches for innovation stimulation and technology management. Consequently, this lecture deepens the knowledge in technology strategy and innovation management (TIM), enables a critical thinking and thought leadership. |
Literature |
1. Course notes and materials provided before the lecture 2. Leiblein/ Ziedonis (2011): Technology Strategy and innovation management. Edward Elgar Publishing Ltd (optional) |
Course L0940: Innovation Management |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | |
Lecturer | Prof. Cornelius Herstatt |
Language | DE/EN |
Cycle | SoSe |
Content |
Innovation is key to corporate growth and sustainibility. In this lecture Prof. Herstatt presents a systematic way from generating ideas to the successful implementation of innovations. The lecture is presented in German language only |
Literature |
|
Course L0161: Internationalization Strategies |
Typ | Project-/problem-based Learning |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 20-30 Minuten Referat einschl. Diskussionsleitung plus schriftliche Ausarbeitung (ca. 10 Seiten) |
Lecturer | Prof. Thomas Wrona |
Language | EN |
Cycle | SoSe |
Content |
|
Literature |
|
Course L2350: Leadership |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | 60 min |
Lecturer | Dr. Thomas Kosin |
Language | DE |
Cycle | WiSe |
Content | |
Literature |
Course L1231: Management and Leadership |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | 60 Minuten |
Lecturer | Prof. Christian Ringle |
Language | DE |
Cycle | SoSe |
Content |
|
Literature |
- Bea, F.X.; Haas, J.: Strategisches Management, 5. Auflage, Stuttgart 2009. |
Course L1857: Entrepreneurial Management |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 20 Minuten inklusive 15 Seiten Ausarbeitung |
Lecturer | Prof. Christoph Ihl |
Language | EN |
Cycle | WiSe |
Content |
Important note: This course is part of an 6 ECTS module consisting of the three courses "Startup Engineering", "Startup Engineering Project" and "Entrepreneurship Management", which have to be taken together in one semester. Startups are temporary, team-based organizations, which can form both within and outside of established companies, to pursue one central objective: taking a new venture idea to market by designing a business model that can be scaled to a full-grown company. In this course, students will form startup teams around self-selected ideas and run through the process just like real startups would do in the first three months of intensive work. Startup Engineering takes an incremental and iterative approach, in that it favors variety and alternatives over one detailed, linear five-year business plan to reach steady state operations. From a problem solving and systems thinking perspective, student teams create different possible versions of a new venture and alternative hypotheses about value creation for customers and value capture vis-à-vis competitors. To test critical hypotheses early on, student teams engage in an evidence-based, experimental trial-and-error learning process that measures real progress. |
Literature |
• Blank, S. & Dorf, B. (2012). The startup owner's manual. |
Course L0863: Marketing |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | |
Lecturer | Prof. Christian Lüthje |
Language | EN |
Cycle | WiSe |
Content |
Contents Basics of Marketing The philosophy and fundamental aims of marketing. Contrasting different marketing fields (e.g. business-to-consumer versus business-to-business marketing). The process of marketing planning, implementation and controlling Strategic Marketing Planning How to find profit opportunities? How to develop cooperation, internationalization, timing, differentiation and cost leadership strategies? Market-oriented Design of products and services How can companies get valuable customer input on product design and development? What is a service? How can companies design innovative services supporting the products? Pricing What are the underlying determinants of pricing decision? Which pricing strategies should companies choose over the life cycle of products? What are special forms of pricing on business-to-business markets (e.g. competitive bidding, auctions)? Marketing Communication What is the role of communication and advertising in business-to-business markets? Why advertise? How can companies manage communication over advertisement, exhibitions and public relations? Sales and Distribution How to build customer relationship? What are the major requirements of industrial selling? What is a distribution channel? How to design and manage a channel strategy on business-to-business markets? Knowledge Students will gain an introduction and good overview of
Skills Based on the acquired knowledge students will be able to:
Social Competence The students will be able to
Self-reliance The students will be able to
|
Literature |
Homburg, C., Kuester, S., Krohmer, H. (2009). Marketing Management, McGraw-Hill Education, Berkshire, extracts p. 31-32, p. 38-53, 406-414, 427-431 Bingham, F. G., Gomes, R., Knowles, P. A. (2005). Business Marketing, McGraw-Hill Higher Education, 3rd edition, 2004, p. 106-110 Besanke, D., Dranove, D., Shanley, M., Schaefer, S. (2007), Economics of strategy, Wiley, 3rd edition, 2007, p. 149-155 Hutt, M. D., Speh, T.W. (2010), Business Marketing Management, 10th edition, South Western, Lengage Learning, p. 112-116 |
Course L2440: Mergers & Acquistions (M&A) |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | 60 min |
Lecturer | Prof. Philipp Haberstock |
Language | DE |
Cycle | SoSe |
Content | |
Literature |
Course L0709: Project Management |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | |
Lecturer | Prof. Carlos Jahn |
Language | EN |
Cycle | WiSe |
Content |
The lecture “project management” aims at characterizing typical phases of projects. Important contents are: possible tasks, organization, techniques and tools for initiation, definition, planning, management and finalization of projects. This will also be deepened by exercises within the framework of the event. The following topics will be covered in the lecture:
|
Literature |
Project Management Institute (2017): A Guide to the Project Management Body of Knowledge (PMBOK® Guide) 6. Aufl. Newtown Square, PA, USA: Project Management Institute. DeMarco, Tom (1997). The Deadline: A Novel About Project Management. DIN Deutsches Institut für Normung e.V. (2009). Projektmanagement - Projektmanagementsysteme - Teil 5: Begriffe. (DIN 69901-5) Frigenti, Enzo and Comninos, Dennis (2002). The Practice of Project Management. Haberfellner, Reinhard (2015). Systems Engineering: Grundlagen und Anwendung Harrison, Frederick and Lock, Dennis (2004). Advanced Project Management: A Structured Approach. Heyworth, Frank (2002). A Guide to Project Management. ISO - International Organization for Standardization (2012). Guidance on Project Management. (21500:2012(E)) Kerzner, Harold (2013). Project Management: A Systems Approach to Planning, Scheduling, and Controlling. Lock, Dennis (2018). Project Management. Martinelli, Russ J. and Miloševic, Dragan (2016). Project Management Toolbox: Tools and Techniques for the Practicing Project Manager. Murch, Richard (2011). Project Management: Best Practices for IT Professionals. Patzak, Gerold and Rattay, Günter (2009). Projektmanagement: Leitfaden zum Management von Projekten, Projektportfolios, Programmen und projektorientierten Unternehmen. |
Course L1385: Project Management in Industrial Practice |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | |
Lecturer | Dipl.-Ing. Wilhelm Radomsky |
Language | DE |
Cycle | WiSe |
Content |
|
Literature |
• Brown (1998): Erfolgreiches Projektmanagement in 7 Tagen • Burghardt (2002): Einführung in Projektmanagement • Cleland / King (1997): Project Management Handbook • Hemmrich, Harrant (2002): Projektmanagement, In 7 Schritten zum Erfolg • Kerzner (2003): Projektmanagement • Litke (2004): Projektmanagement • Madauss (2005): Handbuch Projektmanagement • Patzak / Rattay (2004): Projektmanagement • PMI (2004): A Guide to the Project Management Body of Knowledge • RKW / GPM: Projektmanagement Fachmann • Schelle / Ottmann / Pfeiffer (2005): ProjektManager |
Course L1897: Project Management and Agile Methods |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Fachtheoretisch-fachpraktische Arbeit |
Examination duration and scale | Ausarbeitung eines Projektplans in Kleingruppen (ca. 5-10 Seiten) |
Lecturer | Christian Bussler |
Language | DE |
Cycle | SoSe |
Content |
The Seminar teaches the basics of project management, which constitutes the foundations for technical as well as for business projects. It also includes a sideline about process management. The participants will work on the following questions:
The approaches are not just taught theoretically, but put to use in group work. Through this approach, participants are enabled to work successfully on actual projects - and manage projects later on. As project work is increasingly important in work life, project management is a key skill for job applicants. Main topics of the seminar include:
With the knowledge and experience from the seminar, participants should be able to acquire a basic certificate in project management with relatively little additional effort. The certification is available through institutions like GPM. Participants already start working on their homework paper in the group work. It comprises 5 to 10 pages and a structure plan for the chosen project, which can be done in Excel for example. Ideally, the members of the work groups write their homework paper together. The expected scale of the paper would increase in this case, yet not proportionally with the number of group members (4 participants would be expected to hand in a paper of 15-20 pages). |
Literature |
Hans-D. Litke, Ilonka Kunow; Projektmanagement. 3. Auflage 2015 Georg Patzak, Günter Rattay; Projektmanagement: Projekte, Projektpotfolios, Programme und projektorientierte Unternehmen. 6. Auflage 2014 GPM Deutsche Gesellschaft für Projektmanagement; Kompetenzbasiertes Projektmanagement (PM3): Handbuch für die Projektarbeit, Qualifizierung und Zertifizierung auf Basis der IPMA Competence Baseline Version 3.0. 6. Auflage, 2014 Tom DeMarco; Der Termin: Ein Roman über Projektmanagement. 2007 Jeff Sutherland, Ken Schwaber; Der Scrum Guide. Der gültige Leitfaden für Scrum: Die Spielregeln. Ständig aktualisiert, kostenloser Download auf http://www.scrumguides.org/ Jurgen Appello; Management 3.0: Leading Agile Developers, Developing Agile Leaders. 2010 |
Course L2349: Accounting and Financial Statements |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | 60 min |
Lecturer | Prof. Matthias Meyer |
Language | DE |
Cycle |
WiSe/ |
Content | |
Literature |
Course L1293: Risk Management |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | 60 Minuten |
Lecturer | Dr. Meike Schröder |
Language | DE |
Cycle | WiSe |
Content |
Risks are inherent in every aspect of business, and the ability of managing risks is one important aspect that differentiates successful business leaders from others. There exist various categories of risk, such as credit, country, market, liquidity, operational, supply chain and reputational. Companies are vulnerable to risks. What makes such risks even more complex and challenging to manage is that the risks are often not within the direct control of the business executive. They can exist outside of the company boundary, and yet the impact to the company can be huge. The awareness and knowledge of how to manage risks in companies, will become increasingly important. Some of the main topics covered in this lecture include:
This lecture is presented in German language only. |
Literature |
Brühwiler, B., Romeike, F. (2010), Praxisleitfaden Risikomanagement. ISO 31000 und ONR 49000 sicher anwenden, Berlin: Erich Schmidt. Cottin, C., Döhler, S. (2013), Risikoanalyse. Modellierung, Beurteilung und Management von Risiken mit Praxisbeispielen, 2. überarbeitete und erweiterte Aufl., Wiesbaden: Springer. Eller, R., Heinrich, M., Perrot, R., Reif, M. (2010), Kompaktwissen Risikomanagement. Nachschlagen, verstehen und erfolgreich umsetzen, Wiesbaden: Gabler. Fiege, S. (2006), Risikomanagement- und Überwachungssystem nach KonTraG. Prozess, Instrumente, Träger, Wiesbaden: Deutscher Universitäts-Verlag. Frame, D. (2003), Managing Risk in organizations. A guide for managers, San Francisco: Wiley. Götze, U., Henselmann, K., Mikus, B. (2001), Risikomanagement, Heidelberg: Physica-Verlag. Müller, K. (2010), Handbuch Unternehmenssicherheit. Umfassendes Sicherheits-, Kontinuitäts- und Risikomanagement mit System, 2., neu bearbeitete Auflage, Wiesbaden: Springer. Rosenkranz, F., Missler-Behr, M. (2005), Unternehmensrisiken erkennen und managen. Einführung in die quantitative Planung, Berlin u.a.: Springer. Wengert, H., Schittenhelm F. A. (2013), Coporate Risk Mangement, Berlin: Springer. |
Course L1389: Key Aspects of Patent Law |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | |
Lecturer | Prof. Christian Rohnke |
Language | DE |
Cycle | SoSe |
Content |
Mayor Issues in Patent Law: The seminar covers five mayor issues in german patent law, namely patentatbility, prosecution, ownership and employee inventions, infringement and licensing and other commercila uses. The lecturer will give an introduction to each issue which will be followed by in-depth inquiry by the participants through group work, presentation of results and moderated discussion. |
Literature | wird noch bekannt gegeben |
Course L1491: Startup Engineering |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Fachtheoretisch-fachpraktische Arbeit |
Examination duration and scale | Ausarbeitung einer Geschäftsidee auf 20-30 Seiten (Inhaltsfolien zur detailliierten Dokumentation des Herangehensweise). Bearbeitungsdauer über den ganzen Kurs hinweg 13 Wochen, Zwischen- und Abschlusspräsentation jeweils 15 min plus 15 Diskussion. |
Lecturer | Prof. Christoph Ihl |
Language | EN |
Cycle | WiSe |
Content |
Important note: This course is part of an 6 ECTS module
consisting of the three courses "Startup Engineering", "Startup
Engineering Project" and "Entrepreneurship Management", which have to be
taken together in one semester. Startups are temporary, team-based organizations, which can form both within and outside of established companies, to pursue one central objective: taking a new venture idea to market by designing a business model that can be scaled to a full-grown company. In this course, students will form startup teams around self-selected ideas and run through the process just like real startups would do in the first three months of intensive work. Startup Engineering takes an incremental and iterative approach, in that it favors variety and alternatives over one detailed, linear five-year business plan to reach steady state operations. From a problem solving and systems thinking perspective, student teams create different possible versions of a new venture and alternative hypotheses about value creation for customers and value capture vis-à-vis competitors. To test critical hypotheses early on, student teams engage in an evidence-based, experimental trial-and-error learning process that measures real progress. |
Literature |
• Blank, S. & Dorf, B. (2012). The startup owner's manual. |
Course L1492: Startup Engineering Project |
Typ | Project-/problem-based Learning |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Mündliche Prüfung |
Examination duration and scale | 20 min |
Lecturer | Prof. Christoph Ihl |
Language | EN |
Cycle | WiSe |
Content |
Important note: This course is part of an 6 ECTS module consisting of the three courses "Startup Engineering", "Startup Engineering Project" and "Entrepreneurship Management", which have to be taken together in one semester. Startups are temporary, team-based organizations, which can form both within and outside of established companies, to pursue one central objective: taking a new venture idea to market by designing a business model that can be scaled to a full-grown company. In this course, students will form startup teams around self-selected ideas and run through the process just like real startups would do in the first three months of intensive work. Startup Engineering takes an incremental and iterative approach, in that it favors variety and alternatives over one detailed, linear five-year business plan to reach steady state operations. From a problem solving and systems thinking perspective, student teams create different possible versions of a new venture and alternative hypotheses about value creation for customers and value capture vis-à-vis competitors. To test critical hypotheses early on, student teams engage in an evidence-based, experimental trial-and-error learning process that measures real progress. |
Literature |
• Blank, S. & Dorf, B. (2012). The startup owner's manual. |
Course L2409: Strategic Shared-Value Management |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 30 Minuten |
Lecturer | Dr. Jill Küberling-Jost |
Language | EN |
Cycle | SoSe |
Content | |
Literature |
Course L2295: Strategische Planung mit Planspielen |
Typ | Project-/problem-based Learning |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | |
Lecturer | Dr. Jan Spitzner |
Language | DE |
Cycle | SoSe |
Content | |
Literature |
Course L2410: Technology Entrepreneurship |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 30 Minuten |
Lecturer | Prof. Christoph Ihl |
Language | EN |
Cycle | SoSe |
Content | |
Literature |
Course L1351: Management Consulting |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | |
Lecturer | Gerald Schwetje |
Language | DE |
Cycle | SoSe |
Content |
The Management Consulting lecture teaches students knowledge that is complementary to their technical and business administration studies. They learn the basics of consulting and agent-principal theory and are given an overview of the consulting market. They are also shown how management consulting works and which methodical building blocks (processes) are needed to deal with a client’s concerns and to undertake a consulting process. By means of practical examples students gain an insight into the extensive range of management consultancy services and of functional consulting. |
Literature |
Bamberger, Ingolf (Hrsg.): Strategische Unternehmensberatung: Konzeptionen - Prozesse - Methoden, Gabler Verlag, Wiesbaden 2008 Bansbach, Schübel, Brötzel & Partner (Hrsg.): Consulting: Analyse - Konzepte - Gestaltung, Stollfuß Verlag, Bonn 2008 Fink, Dietmar (Hrsg.): Strategische Unternehmensberatung, Vahlens Handbücher, München, Verlag Vahlen, 2009 Heuermann, R./Herrmann, F.: Unternehmensberatung: Anatomie und Perspektiven einer Dienstleistungselite, Fakten und Meinungen für Kunden, Berater und Beobachter der Branche, Verlag Vahlen, München 2003 Kubr, Milan: Management consulting: A guide to the profession, 3. Auflage, Geneva, International Labour Office, 1992 Küting, Karlheinz (Hrsg.): Saarbrücker Handbuch der Betriebswirtschaftlichen Beratung; 4. Aufl., NWB Verlag, Herne 2008 Nagel, Kurt: 200 Strategien, Prinzipien und Systeme für den persönlichen und unternehmerischen Erfolg, 4. Aufl., Landsberg/Lech, mi-Verlag, 1991 Niedereichholz, Christel: Unternehmensberatung: Beratungsmarketing und Auftragsakquisition, Band 1, 2. Aufl., Oldenburg Verlag, 1996 Niedereichholz; Christel: Unternehmensberatung: Auftragsdurchführung und Qualitätssicherung, Band 2, Oldenburg Verlag, 1997 Quiring, Andreas: Rechtshandbuch für Unternehmensberater: Eine praxisorientierte Darstellung der typischen Risiken und der zweckmäßigen Strategien zum Risikomanagement mit Checklisten und Musterverträgen, Vahlen Verlag, München 2005 Schwetje, Gerald: Ihr Weg zur effizienten Unternehmensberatung: Beratungserfolg durch eine qualifizierte Beratungsmethode, NWB Verlag, Herne 2013 Schwetje, Gerald: Wer seine Nachfolge nicht regelt, vermindert seinen Unternehmenswert, in: NWB, Betriebswirtschaftliche Beratung, 03/2011 und: Sparkassen Firmenberatung aktuell, 05/2011 Schwetje, Gerald: Strategie-Assessment mit Hilfe von Arbeitshilfen der NWB-Datenbank - Pragmatischer Beratungsansatz speziell für KMU: NWB, Betriebswirtschaftliche Beratung, 10/2011 Schwetje, Gerald: Strategie-Werkzeugkasten für kleine Unternehmen, Fachbeiträge, Excel-Berechnungsprogramme, Checklisten/Muster und Mandanten-Merkblatt: NWB, Downloadprodukte, 11/2011 Schwetje, Gerald: Die Unternehmensberatung als komplementäres Leistungsangebot der Steuerberatung - Zusätzliches Honorar bei bestehenden Klienten: NWB, Betriebswirtschaftliche Beratung, 02/2012 Schwetje, Gerald: Die Mandanten-Berater-Beziehung: Erfolgsfaktor Beziehungsmanagement, in: NWB Betriebswirtschaftliche Beratung, 08/2012 Schwetje, Gerald: Die Mandanten-Berater-Beziehung: Erfolgsfaktor Vertrauen, in: NWB Betriebswirtschaftliche Beratung, 09/2012 Wohlgemuth, Andre C.: Unternehmensberatung (Management Consulting): Dokumentation zur Vorlesung „Unternehmensberatung“, vdf Hochschulverlag, Zürich 2010 |
Course L0536: Management of Trust and Reputation |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 20-30 Minuten und Thesenpapier |
Lecturer | Dr. Michael Florian |
Language | DE |
Cycle | SoSe |
Content |
The seminar offers a comparison and analysis of relevant theoretical concepts and practical issues in the corporate management of trust and reputation. Selected case studies will be used to discuss opportunities, problems, and limitations using trust and reputation to coordinate and control economic behavior. |
Literature |
Allgäuer, Jörg E. (2009): Vertrauensmanagement: Kontrolle ist gut, Vertrauen ist besser. Ein Plädoyer für Vertrauensmanagement als zentrale Aufgabe integrierter Unternehmenskommunikation von Dienstleistungsunternehmen. München: brain script Behr. |
Course L1381: Public and Constitutional Law |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | 2 Stunden |
Lecturer | Klaus-Ulrich Tempke |
Language | DE |
Cycle |
WiSe/ |
Content |
Different areas of public law; proceedings, jurisdiction of administrative courts with stages of appeal, |
Literature |
Module M0524: Non-technical Courses for Master |
Module Responsible | Dagmar Richter |
Admission Requirements | None |
Recommended Previous Knowledge | None |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
The Nontechnical Academic Programms (NTA) imparts skills that, in view of the TUHH’s training profile, professional engineering studies require but are not able to cover fully. 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, communication studies, migration 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
|
Skills |
Professional Competence (Skills) In selected sub-areas students can
|
Personal Competence | |
Social Competence |
Personal Competences (Social Skills) Students will be able
|
Autonomy |
Personal Competences (Self-reliance) Students are able in selected areas
|
Workload in Hours | Depends on choice of courses |
Credit points | 6 |
Course L1775: “What’s up, Doc?” Science and Stereotypes in Literature and Film |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Dr. Jennifer Henke |
Language | EN |
Cycle |
WiSe/ |
Content |
Popular novels and films significantly contribute to the public understanding of science and its representatives. How to define “good” or “bad” science is negotiated in a variety of artistic works. Stereotypes such as the “mad scientist”, which originated in early nineteenth century England, continue to persist. Mary Shelley created the prototype of the obsessive and reckless scientist in Frankenstein - The Modern Prometheus (1818) who conducts his forbidden experiments in a secret lab and crosses ethical boundaries. This masculine stereotype has been followed by further ones such as the noble, adventurous or clumsy scientist, whereas scholars have only recently begun to consider the representation of female science. First, this seminar is devoted to selected formations of knowledge in relation to literature from classical antiquity to the present. Second, the focus shall rest on the production of persistent stereotypes in various media formats such as novels or films while paying particular attention to the aspect of gender. The overall goal of the seminar is an understanding of science as a cultural practice. Requirements for participation: Shelley, Mary: Frankenstein. New York: Norton, 2012. Please pay attention to the exact publication dates. |
Literature |
Teilnahmevoraussetzungen: Shelley, Mary: Frankenstein. New York: Norton, 2012. Bitte ausschließlich diese Edition anschaffen. |
Course L2064: 120 years of film history |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | 90 min |
Lecturer | Prof. Margarete Jarchow |
Language | DE |
Cycle | SoSe |
Content | The lecture deals with the relationship between the develpoment of film technology, film aesthetics, and society. Based on the nineteenth-century film's precursors such as the laterna magica, photography and kinetoscope, crucial stages of more than 120 years of film history are studied chronologically in terms of: How does the development of new media techniques reflect certain social changes and needs? What new forms of aesthetic expression are possible through such technical innovations as the introduction of sound film, color film or handheld camera? And to what extent do these new forms of aesthetic expression in turn reflect certain social sensitivities, ultimately the respective zeitgeist? Main topics of the lecture are: the technical euphoria of the 19th century, the early film, the German Expressionist film, the classic Hollywood cinema, the European postwar cinema, exploitation and underground cinema, New Hollywood, the blockbuster cinema, independent cinema up to current phenomena like the „cinema of dissolution“. On the one hand, the participants learn in-depth, detailed knowledge of the history, meaning and analysis of the medium film and thereby acquire media literacy. On the other hand, the participants should gain a deeper understanding of the real interdependencies of technologies in culture and society and their historical transformation processes through an interdisciplinary perspective on film (history of technology, media studies and social science). |
Literature |
Course L1774: Applied Arts: Form and Function |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Prof. Margarete Jarchow, Dr. Christian Lechelt |
Language | DE |
Cycle |
WiSe/ |
Content |
From Arts & Crafts to modern Design - applied arts focus on the design of all kinds of products. Therefore applied arts allow to come to more thorough conclusions about social, historical, cultural issues. In the course the impact of social developments on these particular genres are discussed. |
Literature |
Wird noch angegeben Will be announced in lecture |
Course L2338: Bauhaus architecture - a search for traces |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Dr. Jörg Schilling |
Language | DE |
Cycle |
WiSe/ |
Content |
The
„100 years of bauhaus“ centenery also involved examining the references,
differences and similarities to Hamburg architecture from 1919-1933. |
Literature | wird im Seminar bekanntgegeben |
Course L1882: Facilitating groups in problem-oriented courses |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Fachtheoretisch-fachpraktische Arbeit |
Examination duration and scale | Schriftliche Ausarbeitung (in mehreren Teilen) sowie eine Präsentation, Teilnahme an Gruppendiskussionen |
Lecturer | Siska Simon |
Language | DE |
Cycle |
WiSe/ |
Content |
Content: -
Planning, execution and reflection of an exemplary course unit |
Literature |
Auszüge aus Fachliteratur zu oben genannten Themen werden in der Veranstaltung ausgegeben |
Course L1990: Clash of Cultures. Film and TV series as images of the own and the other |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Jacobus Bracker |
Language | DE |
Cycle |
WiSe/ |
Content |
Images are negotiating concepts of the own, other and alien. Especially tv series like “Game of Thrones”, “Vikings”, or “The Walking Dead” and films like “Alien” or “Lord of the Rings” show clashes of cultures. Irrespective of their genre - fantasy, science fiction, or history - the moving images use always similar patterns to show and tell the own and the other. During the seminar we will deal with such concepts and concepts of culture and the specifics of film and series to watch and analyse selected examples from these perspectives. |
Literature |
Literaturhinweise, Texte etc. werden zu gegebener Zeit online zur Verfügung gestellt. |
Course L1176: The end is near - Survival in the post-apocalypse |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Dr. Marlis Bussacker |
Language | DE |
Cycle |
WiSe/ |
Content |
According to the FAZ in December 2015, the end of the world is booming. At all times, people have dealt with the imminent future scenario of ultimate horror - the collapse of their own world. Where does the idea of a final disaster come from? What's so fascinating about our own demise? During the seminar we will take a look at European cultural history, which is closely linked to mythological and religious prophecies about the end of the world. However, this question, or rather the question of survival in a post-apocalyptic world, has fortunately remained speculative to this day despite regular predictions. Since the end of the world has not yet happened in reality, we are therefore dependent on the imagination of writers, screenwriters and directors who have anticipated the event in an infinite number of texts, films and series. Based on selected films and texts, the seminar will focus on the questions of which apocalyptic scenarios are developed, with which problems the survivors are confronted and how they deal with the situation and with each other. The focus is on the reactions of people in a state of extreme threat. Which survival strategies are presented to us, how do we assess the behaviour of the actors, can we create alternatives? Furthermore, the effect of the genre on the recipient will be discussed. Do we dismiss films like Armaggedon and The Day After Tomorrow as entertaining thrills? Do we just enjoy the special effects? Do we feel threatened? Do we take them in the end as real instructions for action? Do they make us reflect? Or are even current social discourses reflected in the garment of the apocalypse? |
Literature |
Course L1441: German as a Foreign Language for International Master Programs |
Typ | Seminar |
Hrs/wk | 4 |
CP | 4 |
Workload in Hours | Independent Study Time 64, Study Time in Lecture 56 |
Examination Form | Klausur |
Examination duration and scale | |
Lecturer | Dagmar Richter |
Language | DE |
Cycle |
WiSe/ |
Content |
Master’s German course in cooperation with IBH e.V. - Master’s German courses at different levels In the international studies program these are obligatory for non-native speakers of German and for students without a DSH certificate or equivalent TEST-DAF result. Grading after an aptitude test. All other students must sign up for a total of 4 ECTS from the catalog of non-technical supplementary courses. |
Literature | - Will be announced in lectures - |
Course L1884: The Hamburger Speicherstadt - from achievements of engineering to world cultural heritage |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 20 minütiges Referat mit anschließender Diskussion |
Lecturer | Dr. Jörg Schilling |
Language | DE |
Cycle |
WiSe/ |
Content |
The seminar wants to show the problems and challenges for the engineers, who built the Hamburger Speicherstadt and their sustainable architectural solutions, which are still of vital importance and the basis for becoming a world cultural heritage. |
Literature | u.a.: Hamburg und seine Bauten unter Berücksichtigung seiner Nachbarstädte Altona und Wandsbek, hg. vom Architekten- und Ingenieur-Verein zu Hamburg, Hamburg 1890; Karin Maak: Die Speicherstadt im Hamburger Hafen, Hamburg 1895; Hermann Hipp: Freie und Hansestadt Hamburg, Köln 1989; Matthias von Popowski: Franz Andreas Meyer (1837-1901). Oberingenieur und Leiter des Ingenieurwesens von 1872-1901, in: Wie das Kunstwerk Hamburg entstand, hg. v. Dieter Schädel, Hamburg 2006, S. 64-79; Ralf Lange: HafenCity + Speicherstadt : das maritime Quartier in Hamburg, Hamburg 2010. |
Course L1996: Digital culture(s): from subculture to media mainstream |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Dr. Oliver Schmidt |
Language | DE |
Cycle |
WiSe/ |
Content |
The course gives an introduction to the development of digitization in a media cultural perspective. In addition to technical aspects, we will focus on the cultural impact of digitization for current media users and the ermergence und development of media subcultures from the late 1970s to the 21st century. On the one hand, we will deal with questions such as: What is digitization? What is culture? What are digital (sub)cultures? In this context, the concept of ‚digital natives‘ and ‚digital immigrants‘, coined by Marc Prensky, will also be discussed. On the other hand, there will be a historical perspective on topics and developments such as the mediatization oft he children’s room in the early 1980s, the hacker scene, video game culture, the demo scene, digital culture in cinema, 8-bit culture, digital aesthetics , net art, post-digitality and ultimately the question of how digital subcultures have become part of the media mainstream at the beginning of the 21st century. |
Literature |
Course L2367: Digital art |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | Referat ca. 20 min. plus anschließende Diskussion |
Lecturer | Dr. Imke Hofmeister |
Language | DE |
Cycle |
WiSe/ |
Content |
Digitalization is having a major impact on many areas of our lives and the use of digital technologies in art and design has increased rapidly. After all, art is not only subject to constant change, but also constantly adapts to technical conditions. After the photographic art of the mid-19th century and the video art of the 1960s, which already brought about major changes in artistic creation, digital art is becoming increasingly important in the field of media art. The first attempts to use the computer with corresponding graphic software as an artistic medium took place in the 80/90s of the 20th century. Since then, there has been a broad development in the field of digital art, which now encompasses the most diverse digital pictorial phenomena and art genres and is thus intertwined in its objects, theories and practices with digital media in a variety of ways. The seminar gives an overview of the history of digital art and its different genres. These include, for example, photopaintings, where digital manipulation, filtering processes and painting can process the image and transform it over many stages into a completely new form. Also 3-D images, vector graphics, mathematical art and computer art in general. At the same time, the digital development in art is to be illuminated, from the first beginnings on the computer with comparatively simple "digital aids", e.g. in the form of simple image processing programs, to the present sophisticated graphic tools. In addition, the presentation, dissemination and conservation possibilities of digital art will also be discussed, which can be disseminated very well on the Internet primarily because it can be displayed on a computer screen. The great fascination with digital creative work and the almost inexhaustible possibilities offered by the medium of computers to artists, who will continue to ensure that digital art finds a permanent place alongside traditional media, will also be discussed. Finally, in contrast to the traditional production methods in the field of fine arts and design, there are always new manifestations of digital art, which ultimately give not only the "trained" artist but also the layman far-reaching possibilities for artistic expression. And all this in the spirit of the performance artist Joseph Beuys , who postulated, every human being is capable of creativity, indeed "every human being is an artist". The seminar will also discuss the question of how digital art can be described as "the" contemporary art, i.e. contemporary art in the age of digital technology. Furthermore, it is of great interest to what extent the perception of art per se has already changed and will continue to change in a digitalized society. |
Literature | folgt |
Course L1725: Introduction to the Science & Technoloy Studies (STS) |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | Gruppenreferat (30 bis 45 Minuten, Eigenanteil je Person 10 bis 15 Minuten) inkl. schriftlicher Ausarbeitung, Ggf. alternativ eine längere, schriftliche Ausarbeitung. |
Lecturer | Dr. Simon Egbert |
Language | EN |
Cycle |
WiSe/ |
Content |
Since the end of the 1980’s or the beginning of the 1990’s, in the Sociology of Technology a line of research has emerged which initially called for a socialization of the sociology of technology (especially through the Social Construction of Technology Approach [SCOT]) and right away called for its re-materialisation (especially through Bruno Latour and the Actor-Network Theory). Technologies, thus their basic idea, are always intertwined with society and shaped by their socio-cultural context. In reverse, society is also inherently formed by the existing technologies and an adequate sociology of technology has to deal especially with the interaction of both. In the seminar at hand first of all an overview shall be given about the classical sociology of technology which routinely used argumentations inspired by technological determinism, which shall be followed by the presentation of the SCOT-approach. The later in turn was criticised by the Actor-Network Theory (which will be presented in a separate section as well) as being social deterministic which has led to a rather heated debate about the agency of technological artefacts, which shall be presented and discussed in a further part of the seminar. In the last section of the class it shall be determined what kind of relevance the sociological analysis of technological artefacts and their societal embedding can or could implicate for the own lifeworld of the students - especially of course with special focus on their engineer studies. |
Literature |
Bammé, Arno (2009): Science and Technology Studies: ein Überblick. Marburg: Metropolis. Degele, Nina (2002): Einführung in die Techniksoziologie. München: Fink. Hackett, Edward et al. (Hrsg.) (2008): The Handbook of Science and Technology Studies. 3rd Edition. Cambridge: MIT Press. Häußling, Roger (2014): Techniksoziologie. Baden-Baden: Nomos. MacKenzie, Donald/Judy, Wajcman (2003): The social shaping of technology. 2nd Edition. Maidenhead et al.: Open University Press. Sismondo, Sergio (2010): An Introduction to Science and Technology Studies, 2nd Edition. Chichester: Wiley-Blackwell. |
Course L2336: Introduction to Marxian Theory of Economy |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | 90 min |
Lecturer | Dr. Martin Schütz |
Language | DE |
Cycle |
WiSe/ |
Content |
Capitalism - what’s the definition in Marxian economical theorie? Which are the functions of gold, money, interest? |
Literature |
Karl Marx, Das Kapital, Band 1, Berlin 1962ff (=Marx-Engels-Werke [MEW] Bd. 23), S. 1-390 Altvater, Elmar (Hg.) (1999): Kapital.doc. Das Kapital (Bd. 1) von Marx in Schaubildern mit Kommentaren. Mit CD-ROM. Münster |
Course L1994: Facts, Facts, Facts - Understanding and Applying Techniques of Journalism - in German |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Prof. Margarete Jarchow, Matthias Kowalski |
Language | DE |
Cycle |
WiSe/ |
Content | Regardless of whether it is via classic channels such as newspapers and magazines or radio and TV as well as via internet, social media or via communication in specialist circles: Today we encounter journalism in almost all forms of public and private communication. But what makes a story really important in this flood of content? How do we recognize relevance? How do we expose fake news? In this block seminar the principles of journalistic techniques are imparted by means of practical examples and editorial exercises. The participants also develop tools to detect and deactivate manipulation and fake news. Regular attendance and attendance at all block dates is required. |
Literature |
Course L2370: Facts, Facts, Facts - Understanding and Applying Techniques of Journalism - in English |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Prof. Margarete Jarchow |
Language | EN |
Cycle |
WiSe/ |
Content |
Regardless of whether it is via classic channels such as newspapers and magazines or radio and TV as well as via internet, social media or via communication in specialist circles: Today we encounter journalism in almost all forms of public and private communication. But what makes a story really important in this flood of content? How do we recognize relevance? How do we expose fake news? In this block seminar the principles of journalistic techniques are imparted by means of practical examples and editorial exercises. The participants also develop tools to detect and deactivate manipulation and fake news. Regular attendance and attendance at all block dates is required. |
Literature | folgt |
Course L0970: Foreign Language Course |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Klausur |
Examination duration and scale | 60 min |
Lecturer | Dagmar Richter |
Language | |
Cycle |
WiSe/ |
Content |
In the Field of the Nontechnical Complementary Courses students are able to chose foreign language courses. Therefore the Hamburger Volkshochschule offers a special language programm on TUHH campus for TUHH Students. It includes courses in english, chinese, french, japanese, portuguese, russia, swedish, spanisch and german as a foreign language. All lectures impart common language knowledge, english courses although english for technical purposes. |
Literature | Kursspezifische Literatur / selected bibliography depending on special lecture programm. |
Course L0983: Management and Communication |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 90-minütige interaktive Präsentation im Team inkl. Handout. |
Lecturer | Wibke Derboven |
Language | DE |
Cycle | SoSe |
Content |
The seminar will present basic elements of personality-promoting work organisation, motivation theories, different management concepts, communication theories and approaches to conflict and knowledge management. These subjects are applied to specific practical examples. Participants are given the opportunity to reflect on their own communicative and social behaviour. |
Literature |
Große Boes, Stefanie; Kaseric, Tanja (2010): Trainer-Kit. Die wichtigsten Trainings-Theorien, ihre |
Course L1883: Guest, barbarian or subject with equal rights? ‘The refugee’ in the history of ‘Western’ political ideas. |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 5-10 Minuten Vortrag im Rahmen eines Gruppenreferats; anschließend Diskussion |
Lecturer | Dr. Simone Beate Borgstede |
Language | DE/EN |
Cycle |
WiSe/ |
Content |
The seminar discusses concepts of ‘the refugee’ in the history of ‘Western’ political ideas over a period of about 2,750 years. We will try to understand these concepts as historically distinct. We will also analyze the powerful effect of related stereotypes and images. We will read and contextualize philosophical, sociological, juridical, literary and political texts. In the second part of the seminar we will use the patterns we found to understand actual discourses on flight and migration. One aim is also to recognize alternative representations in the articulations and practices of the refugees themselves. |
Literature |
Agamben, Giorgio, ‚Homo Sacer: Die souveräne Macht und das nackte Leben.’ Arendt, Hannah, ‚Wir Flüchtlinge’ und ‚Das Recht, Rechte zu haben’. Aristoteles, Politik und Platon, Politeia (Auszüge). Derrida, Jacques, ‚Weltbürger aller Länder, noch eine Anstrengung!’ Erpenbeck, Jenny: Gehen, ging, gegangen. Roman. Genfer Konvention und Menschenrechtserklärung. Homer, Die Odyssee. Simmel, Georg, ‚Exkurs über den Fremden’. Dazu kommen Textstellen aus Bibel und Koran, aktuelle Interviews mit Migrationsforscher_innen wie Manuela Bojadzijev und Vassilis Tsianos, aber auch Erklärungen von Geflüchteten-Gruppen, Musiktexte, Fotographien und Filmspots. |
Course L1844: Stay cool in conflict. Nonviolent Communication by Marshall Rosenberg |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 2-3 Seiten bzw. 10-20 Minuten plus anschließende Besprechung |
Lecturer | Dr. Claudia Wunram |
Language | EN |
Cycle |
WiSe/ |
Content |
„Words can build bridges or create rafts“ - this is also true for the scientific and business world. For example, how do I react if I get attacked in a professional debate by an opponent or by a colleague in my team, or if a fight arises during the planning of a project? In a challenging situation, what will help me to communicate respectfully and with appreciation? How can I express criticism or irritation honestly, directly and without reproach? Nonviolent Communication is a concept developped by Marshall B. Rosenberg, Ph.D., intended to help create an appreciative attitude towards oneself and others, and to live by it. Nonviolent Communication opens paths to express oneself in a mindful and responsible way, so that a bridge can be built even in challenging situations of conflict. Effective and satisfactory cooperation is only possible with well functioning communication between all parties involved, otherwise things will become difficult and inefficient. By working with their own examples and anticipating questions that might arise in their future professional lives, the students of Engineering Sciences will be able to reflect their own communicative behavior and learn ways of cooperation and conjoint solution finding. This course will impart the essential competencies of communication necesary for that. |
Literature |
German:
English:
|
Course L2345: Theory, Research and Practice of University Teaching |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Fachtheoretisch-fachpraktische Arbeit |
Examination duration and scale | Schriftliche Ausarbeitung (in mehreren Teilen) sowie eine Präsentation |
Lecturer | Prof. Christian Kautz, Jenny Alice Rohde |
Language | DE |
Cycle |
WiSe/ |
Content |
This course covers theory and practice of being a student teaching assistant in small-group instructional settings at TUHH. As part of the seminar, the participants have the opportunity to reflect on their work, e. g. through mutual observation and discussion. For prior knowledge / the event requirements: This event requires basic first work / collaboration experiences in the academic work structures of a higher education institution, which Master's students have acquired as part of the qualification for the Bachelor's degree at a university. These presumed work experiences include specific self-study experiences at a college. These are picked up, reflected, expanded and further developed both theoretically and practically with regard to learning from and in groups and later guiding this learning process. Furthermore, experiences with different types of learning / group types of higher education, which are part of a degree program acquired during the bachelor's program, are assumed, taken up, reflected on, expanded and further developed here in the master's program. The course also requires basic knowledge of presenting scholarly work results obtained by Master's students with a Bachelor's degree. In the course, this experience with and in representation in a group situation will be expanded and further developed in the direction of students' involvement with their own role as well as their design in face-to-face interaction as well as in group processes, learning and leadership situations, as masters graduates Graduate unlike bachelor graduates professionally stronger in a moderating role and with the guidance of humans because with the guidance in subject matters are demanded. According to the later professional role, the work of the seminar promotes and enables graduate students significantly more than graduates' qualifications for independent work and learning, transferring what they have learned to new areas, contributing, involving discussion and contributing their own examples and interests. |
Literature |
Auszüge aus Fachliteratur zu oben genannten Themen werden in der Veranstaltung ausgegeben. Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman. Bosse, E. (2016). Herausforderungen und Unterstützung für gelingendes Studieren: Studienanforderungen und Angebote für den Studieneinstieg. In I. van den Berk, K. Petersen, K. Schultes, & K. Stolz (Hrsg.). Studierfähigkeit - theoretische Erkenntnisse, empirische Befunde und praktische Perspektiven (Bd. 15). (S.129-169). Hamburg: Universität Hamburg. Collins, D. & Holton, E. (2004). The effectiveness of managerial leadership development programs: A meta-analysis of studies from 1982 to 2001. Human resource development quarterly, 15(2), 217 - 248. Danielsiek, H., Hubwieser, P., Krugel, J., Magenheim, J., Ohrndorf, L., Ossenschmidt, D., Schaper, N. & Vahrenhold, J. (2017). Verbundprojekt KETTI: Kompetenzerwerb von Tutorinnen und Tutoren in der Informatik. In A. Hanft, F. Bischoff, B. Prang (Hrsg.), Working Paper Lehr-/Lernformen. Perspektiven aus der Begleitforschung zum Qualitätspakt Lehre. Abgerufen von KoBF: Freeman, S., Eddy, SL., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H. & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematic. Proceedings of the National Academy of Sciences 11(23), 8410-8415. Glathe, A. (2017). Effekte von Tutorentraining und die Kompetenzentwicklung von MINTFachtutor* innen in Lernunterstützungsfunktion. (Nicht veröffentlichte Dissertation). Technische Universität Darmstadt, Deutschland. Kirkpatrick, D. L. (1959). Techniques for Evaluation Training Program. Journal of the American Society of Training Directors, 13, 21-26. Hänze, M. Fischer, E. Schreiber, Biehler, R. & Hochmuth, R- (2013). Innovationen in der Hochschullehre: empirische Überprüfung eines Studienprogramms zur Verbesserung von vorlesungsbegleitenden Übungsgruppen in der Mathematik. Zeitschrift für Hochschulentwicklung, 8(4), 89- 103. Kröpke, H. (2014). Who is who? Tutoring und Mentoring - der Versuch einer begrifflichen Schärfung. In D. Lenzen & H. Fischer (Hrsg.), Tutoring und Mentoring unter besonderer Berücksichtigung der Orientierungseinheit (Bd. 5). (21-29). Hamburg: Universitätskolleg-Schriften. Kühlmann, T. (2007). Fragebögen. In J. Straub, A. Weidemann & D. Weidemann (Hrsg.), Handbuch interkulturelle Kommunikation und Kompetenz (346-352). Stuttgart: Metzler. Mayring, P. (2010). Qualitative Inhaltsanalyse. Grundlagen und Techniken (11. aktualisierte und überarbeitete Auflage). Weinheim/Basel: Beltz. Mummendey, H. D. (1981). Methoden und Probleme der Kontrolle sozialer Erwünschtheit (Social Desirability). Zeitschrift für Differentielle und Diagnostische Psychologie, 2, 199-218. Rohde, J. & Block, M. (2018). Welche Herausforderungen und Bewältigungsstrategien berichten Tutor/innen der Ingenieurwissenschaften? Eine explorative Analyse von Reflexionsberichten. Vortrag auf der 47. Tagung der Deutschen Gesellschaft für Hochschuldidaktik, Karlsruhe. Heterogenität der Studierenden und Lösungsansätze von Tutor/-innen Jenny Alice Rohde. Posterpräsentation auf der Tagung “Tutorielle Lehre und Heterogenität”. Technische Universität Darmstadt, 16.05.2019.Hochschuldidaktische Tutorenqualifizierung - Eine Basisqualifizierung des akademischen Nachwuchses und Chance für den Wandel der Lehr-/Lernkultur? Jenny Alice Rohde & Caroline Thon-Gairola. Posterpräsentation auf der DGHD am 07.03.2019.Welches Lehrverhalten zeigen geschulte Tutor/innen? Eine explorative Analyse selbst- und fremdwahrnehmungsbasierter Reflexionsberichte Jenny Alice Rohde & Nadine Stahlberg. In: die hochschulehre (2019). Schneider, M. & Preckel, F. (2017). Variables associated with achievement in higher education: A systematic review of meta-analyse. Psychological Bulletin, 143(6), 565-600. Skylar Powell, K. & Yalcin, S. (2010). Managerial training effectiveness: A meta-analysis 1952-2002. Personnel Review, 39(2), 227-241. 27 Welches Lehrverhalten zeigen geschulte Tutor/innen d ie hochs chul l ehre 2019 www.hochschullehre.org Stes, A., Min-Leliveld, M., Gijbels, D. & Van Petegem, P. (2010). The impact of instructional development in higher education: The state-of-the-art of the research. Educational Research Review, 5(1), 25-49. Stroebe, W. (2016). Why Good Teaching Evaluations May Reward Bad Teaching: On Grade Inflation and Other Unintended Consequences of Student Evaluation. Perspectives on Psychological Science, 11(6), 800-816. Technische Universität Hamburg (2018). Kennzahlen 2017. Hamburg: Technische Universität Hamburg. [https://www.tuhh.de/tuhh/uni/informationen/kennzahlen.html] Thumser-Dauth, K. (2008). Und was bringt das? Evaluation hochschuldidaktischer Weiterbildung. In B. Berendt, H.-P. Voss & J. Wildt (Hrsg.), Neues Handbuch Hochschullehre. Lehren und Lernen effizient gestalten. Kap. L 1.11 Hochschuldidaktische Aus- und Weiterbildung. Veranstaltungskonzepte und -modelle. Berlin: Raabe. S. 1-10. Wibbecke, G. (2015): Evaluation einer hochschuldidaktischen Weiterbildung an der Medizinischen Fakultät Heidelberg. Dissertation. Ruprecht-Karls-Universität Heidelberg. Willige, J., Woisch, A., Grützmacher, J. & Naumann, H. (2015a). Randauszählung Studienqualitätsmonitor 2014, Technische Universität Hamburg-Harburg, Online-Befragung Studierender im Sommersemester 2014, DZHW - Deutsches Zentrum für Hochschul- und Wissenschaftsforschung. Willige, J., Woisch, A., Grützmacher, J. & Naumann, H. (2015b). Randauszählung Studienqualitätsmonitor 2015, Technische Universität Hamburg-Harburg, Online-Befragung Studierender im Sommersemester 2015, DZHW - Deutsches Zentrum für Hochschul- und Wissenschaftsforschung. Winkler, M. (2018). Tutorielle Lehransätze im Vergleich. Die KOMPASS Begleitforschung. Vortrag gehalten am 12.03.2018 auf dem Netzwerktreffen Tutorienarbeit an Hochschulen in Würzburg. Zech, F. (1977). Grundkurs Mathematikdidaktik: theoretische und praktische Anleitungen für das Lehren und Lernen im Fach Mathematik. Weinheim: Beltz. |
Course L1509: Intercultural Communication |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Prof. Margarete Jarchow, Anna Katharina Bartel |
Language | EN |
Cycle |
WiSe/ |
Content |
As young professionals with technical background you may often tend to focus on communicating numbers and statistics in your presentations. However, facts are only one aspect of convincing others. Often, your personality, personal experience, cultural background and emotions are more important. You have to convince as a person in order to get your content across. In this workshop you will learn how to increase and express your cultural competence. You will apply cultural knowledge and images in order to positively influence communicative situations. You will learn how to add character and interest to your talks, papers and publications by referring to your own and European Cultural background. You will find out the basics of communicating professionally and convincingly by showing personality and by referring to your own cultural knowledge. You will get hands-on experience both in preparing and in conducting such communicative situations. This course is not focussing on delivering new knowledge about European culture but helps you using existing knowledge or such that you can gain e.g. in other Humanities courses. Content
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Literature |
Literaturhinweise werden zu Beginn des Seminars bekanntgegeben. Literature will be announced at the beginning of the seminar. |
Course L2015: Intercultural Management - Theory and Awareness Training |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Schriftliche Ausarbeitung |
Examination duration and scale | 15 Minuten Vortrag und dessen schriftliche Ausarbeitung (10 Seiten) |
Lecturer | Prof Jürgen Rothlauf |
Language | EN |
Cycle |
WiSe/ |
Content |
The subject of the course is the deepening of the intercultural dimension of international management in relation to fundamental challenges, the importance of culture in team work and leadership of large multinational companies. In addition, culture-awareness trainings are discussed and carried out. |
Literature |
Rothlauf, J (2014): A Global View on Intercultural Management - Challenges in a Globalized World, De Gruyter Oldenbourg Verlag, 360 p |
Course L2346: Young, educated, (non)political - are our young engineers well prepared for the future? |
Typ | Seminar | |
Hrs/wk | 2 | |
CP | 2 | |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 | |
Examination Form | Referat | |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion | |
Lecturer | Vincent-Immanuel Herr | |
Language | DE | |
Cycle |
WiSe/ |
|
Content |
Digitalization, climate change, democracy - society is facing fundamental upheavals. The next generation of young engineers in particular must no longer remain out of debate and can provide answers to the big questions of our time. Why is social commitment important? Is studying preparing us well for the future? What needs to improve? In the interactive workshop, the participants will be accompanied in analyzing their own generation and their own actions and in developing thesis on how to improve technical studies and training. The result of the seminar will be a joint thesis paper. |
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Literature |
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Course L2176: Culture of Communication - Theories and Methods of Successful Communication |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Anna Katharina Bartel |
Language | DE |
Cycle |
WiSe/ |
Content |
This course is for master students. In this seminar, we will explore different theories, models and methods from the fields of communication, psychology and cultural theory. The participants will work on theoretical content and do group presentations. They will also use examples from their own experiences to apply models and methods in practical exercises. The way we communicate shapes the way we experience our relationships, in the business world as well as in our private lives. We spend an overwhelming amount of time in group situations. This makes it worthwhile to explore how communication works within the group context and how, within these different groups, different cultures of communication develop. This particularly applies in highly specialized fields, such as engineering. Our ability to flexibly and successfully move from one context to another helps us along in building successful careers and allows us to feel positive about our private lives. However, this is not always simple. For example: If we are part of a context in which many conflicts arise If we have to switch between different contexts frequently Or if, on the one hand, complicated facts and data are our main focus but on the other hand, we have to communicate them to people who are not familiar with the subject. Maybe we even have to win their attention in order to help along our causes. Oftentimes, this leads to misunderstandings. There also might be a lack of openness or willingness to embrace conflict. This might make it difficult for us to reach our goals. To be able to reflect on the way we communicate, to identify patterns of communication and the ability to actively build positive relationships through communication are useful skills to help overcome those obstacles.. |
Literature |
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Course L0535: Theory of Communication |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | 20-30 Minuten Referat und Thesenpapier |
Lecturer | Dr. Michael Florian |
Language | DE |
Cycle | SoSe |
Content |
The seminar focuses on sociological theories of communication and selected problems of practical application in the area of crisis communication. The issue of crisis communication will be analyzed on the basis of case studies. |
Literature |
Habermas, Jürgen (1981): Theorie des kommunikativen Handelns. 2 Bände. Frankfurt/Main: Suhrkamp. |
Course L1732: criminology and society - in German |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | Gruppenreferat (30 bis 45 Minuten, Eigenanteil je Person 10 bis 15 Minuten) inkl. schriftlicher Ausarbeitung, Ggf. alternativ eine längere, schriftliche Ausarbeitung. |
Lecturer | Sarah Schirmer |
Language | DE |
Cycle |
WiSe/ |
Content |
The seminar will provide an overview of Criminology and introduce different |
Literature |
Wird zeitnah bekannt gegeben. Will be announced in lecture. |
Course L2369: Literature and Culture for international students of Master's degree programs in English (non-native speakers of German) |
Typ | Seminar |
Hrs/wk | 4 |
CP | 4 |
Workload in Hours | Independent Study Time 64, Study Time in Lecture 56 |
Examination Form | Referat |
Examination duration and scale | 45 min. Präsentation und anschließende Diskussion |
Lecturer | Bertrand Schütz |
Language | DE |
Cycle |
WiSe/ |
Content |
The seminar LITERATURE AND CULTURE investigates what culture is, especially what characterises epistemic cultures. Culture is to be understood as the creative response to a given situation and the capacity to integrate inputs and influences, therefore as an ongoing process of permanent readjustment and learning, and by no means as a fixed identity in terms of an “essence”. There is a growing awareness that Europe cannot lay claim to possess the ultimate standards of knowledge. A topography of our contemporary world is to be sketched by highlighting its historical and cultural premises. For more information please refer to the German description and the StudIP. |
Literature |
Je nach Thematik des Semesters wird eine spezifische cf. StudIP |
Course L1837: People in Business Organizations |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Schriftliche Ausarbeitung |
Examination duration and scale | Schriftliche Hausarbeit 7-10 Textseiten; verpflichtend: Präsentation der Zwischenergebnisse mit Diskussion (geht nicht in die Bewertung mit ein) |
Lecturer | Dr. Martin Schütz |
Language | DE |
Cycle |
WiSe/ |
Content |
The influence of technological change and social change on business organizations - how to manage the organizational change. |
Literature |
Becker, Karen Louise (2007): Unlearning in the workplace. A mixed methods study. PhD. Queensland University of Technology, Brisbane. Faculty of Education. Online verfügbar unter http://eprints.qut.edu.au/16574/. Frey, Dieter; Gerkhardt, Marit; Peus, Claudia; Traut-Mattausch, Eva; Fischer, Peter (2014): Veränderungen managen. Widerstände und Erfolgsfaktoren der Umsetzung. In: Lutz von Rosenstiel, Erika Regnet und Michel E. Domsch (Hg.): Führung von Mitarbeitern. Handbuch für erfolgreiches Personalmanagement. 7. Aufl. Stuttgart: Schäffer-Poeschel, S. 547-559. Hauser, Berndhard (2014): Konflikte in und zwischen Gruppen. In: Lutz von Rosenstiel, Erika Regnet und Michel E. Domsch (Hg.): Führung von Mitarbeitern. Handbuch für erfolgreiches Personalmanagement. 7. Aufl. Stuttgart: Schäffer-Poeschel, S. 354-367. Kieser, Alfred; Walgenbach, Peter (2007): Organisation. 5. Aufl. Stuttgart: Schäffer-Poeschel. Miebach, Bernhard (2012): Organisationstheorie. Problemstellung - Modelle - Entwicklung. 2. Aufl. Wiesbaden: Springer Fachmedien Wiesbaden; Imprint: Springer VS. Müller, Ursula (Hg.) (2013): Geschlecht und Organisation. Wiesbaden: Springer VS (Geschlecht und Gesellschaft, 45). Olfert, Klaus (2012): Organisation. 16. Aufl. Herne: NWB Verlag. Pohlmann, Markus; Markova, Hristina (2011): Soziologie der Organisation. Eine Einführung. Konstanz, München: UVK-Verl.-Ges. (3573). Preisendörfer, Peter (2011): Organisationssoziologie. Grundlagen, Theorien und Problemstellungen. 3. Aufl. Wiesbaden: VS Verlag für Sozialwissenschaften. Robbins, Stephen P.; Judge, Timothy A. (2013): Organizational Behavior. 15. Aufl. Boston, Mass: Pearson. Rosenstiel, Lutz von; Nerdinger, Friedemann W. (2011): Grundlagen der Organisationspsychologie. Basiswissen und Anwendungshinweise. 7. Aufl. Stuttgart: Schäffer-Poeschel. Sanders, Karin; Kianty, Andrea (2006): Organisationstheorien. Eine Einführung. 1. Aufl. Wiesbaden: VS Verlag für Sozialwissenschaften. Schreyögg, Georg (2008): Organisation. Grundlagen moderner Organisationsgestaltung, mit Fallstudien. 5. Aufl. Wiesbaden: Gabler (Lehrbuch). Vahs, Dietmar (2012): Organisation. Ein Lehr- und Managementbuch. 8. Aufl. Stuttgart: Schäffer-Poeschel. Weinert, Ansfried B. (2004): Organisations- und Personalpsychologie. 5. Aufl. Weinheim: BeltzPVU. |
Course L1846: Classical Journalism and New Media |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | Ca. 20 min. plus anschließende Diskussion |
Lecturer | Dieter Bednarz |
Language | DE |
Cycle |
WiSe/ |
Content |
The world wide walkover of the internet dramatically changed the perception of classical media like newspapers, magazines and even TV. In this seminar the reasons of and the consequences for the dramatic changes regarding our information habits will be analyzed and discussed. Has the media expert Neil Postman been right, when he one said, that we all one day will be „overnewsed but underinformed“? Keeping a close eye on the real challenges of journalism, the seminar will discuss the standards of ethics in politics and media. |
Literature |
Wird im Seminar genannt |
Course L1023: Politics |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Dr. Stephan Albrecht |
Language | EN |
Cycle |
WiSe/ |
Content |
Scientists and engineers neither just strive for truths and scientific laws, nor are they working in a space far from politics. Science and engineering have contributed to what we now call the Anthropocene, the first time in the history of mankind when essential cycles of the earth system, e.g. carbon cycle, climate system, are heavily influenced or even shattered. Furthermore, Peak oil is indicating the end of cheap fossil energy thus triggering the search for alternatives such as biomass. Systems of knowledge, science and technology in the OECD countries have since roughly 30 years increasingly become divided. On the one hand new technologies such as modern biotechnology, IT or nanotechnology are developing rapidly, bringing about many innovations for industry, agriculture, and consumers. On the other hand scientific studies from earth, environmental, climate change, agricultural and social sciences deliver increasingly robust evidence on more or less severe impacts on society, environment, global equity, and economy resulting from innovations during the last 50 years. Technological innovation thus is no longer an uncontested concept. And many protest movements demonstrate that the introduction of new or the enlargement of existing technologies (e.g. airports, railway stations, highways, high-voltage power lines surveillance) isn’t at all a matter of course. It is important to bear in mind the fact that all processes of technological innovation are made by humans, individually and collectively. Industrial, social, and political organizations as actors from the local to global level of communication, deliberation, and decision making interact in diverse arenas, struggling to promote their respective corporate and/or political agenda. So innovations are as well a problem of technology as a problem of politics. Innovation and technology policies aren’t the same in all countries. We can observe conceptual and practical variations. Since the 1992 Earth Summit in Rio de Janeiro Agenda 21 constitutes a normative umbrella, indicating Sustainable Development (SD) as core cluster of earth politics on all levels from local to global. Meanwhile other documents such as the Millennium Development Goals (MDG) have complemented the SD agenda. SD can be interpreted as operationalization of the Universal Declaration of Human Rights, adopted in 1948 by the General Assembly of the United Nations and since amended many times. Engineers and scientists as professionals can’t avoid to become confronted with many non-technical and non-disciplinary items, challenges, and dilemmas. So they have to choose between alternative options for action, as individuals and as members of organizations or employees. Therefore the seminar will address core elements of the complex interrelations between science, society and politics. Reflections on experiences of participants - e.g. from other countries as Germany - during the seminar are very welcome. The goals of the seminar include:
The seminar will deal with current problems from areas such as innovation policy, energy, food systems, and raw materials. Issues will include the future of energy, food security and electronics. Historical issues will also be addressed. The seminar will start with a profound overarching introduction. Issues will be introduced by a short presentation and a Q & A session, followed by group work on selected problems. All participants will have to prepare a presentation during the weekend seminar. The seminar will use inter alia interactive tools of teaching such as focus groups, simulations and presentations by students. Regular and active participation is required at all stages. |
Literature | Literatur wird zu Beginn des Seminars abgesprochen. |
Course L1856: Politics and Science - in German |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | Referat ca. 20 min. plus anschließende Diskussion |
Lecturer | Dr. Mirko Himmel, Dr. Ines Krohn-Molt |
Language | DE |
Cycle |
WiSe/ |
Content |
Scientists often like to believe that their work is non-political. Within this seminar we want to demonstrate how deeply both are interconnected and converged. Not only, scientific guidance is often needed to take a political decision but also scientific outcomes are a sub-ject to political interpretation. Also, politics are significantly influencing scientific progress by framing research agendas and by funding decisions. |
Literature |
Wird im Seminar genannt |
Course L1779: Politics and Science - in English |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Dr. Frederik Postelt, Dr. Gunnar Jeremias |
Language | EN |
Cycle |
WiSe/ |
Content |
Scientists often like to believe that their work is non-political. Within this seminar we want to demonstrate how deeply both are interconnected and converged. Not only, scientific guidance is often needed to take a political decision but also scientific outcomes are a sub-ject to political interpretation. Also, politics are significantly influencing scientific progress by framing research agendas and by funding decisions. During this seminar we would like to show the different range of influences - scientific, economic, social, environmental, ethical/normative, security-related - affecting decision-making on science and politics. Using case studies on current debates on food security, public health, nuclear energy and terrorism to discuss the interrelation between science and politics illuminating the role of various actors in this process, such as: • Governments, • International organizations, • Scientific associations, • Industry, • Civil society, and • Individual scientists. The guiding questions will be: • How does and should science influence politics? • How does and should politics influence science? In order to take responsibility for the consequences of scientific work, engineers and scientists increasingly need to acknowledge the political dimension of their work and their role in the political process. We will address this political dimension of scientific work by discussing: • Biographies and motivations of famous scientists, • Individual responsibility of scientists for the implications of their work, and • The role of codes of conduct as guidelines for responsible behaviour. The goals of the seminar include: • Raising awareness and increasing knowledge about the political dimensions of scientific work, • Providing guidelines for evaluating political implications of scientific research, • Improving the understanding of scientists’ and engineers’ responsibility for the results of their professional activities, • Taking decisions at the institutional, national and international level about rules and regulations concerning scientific conduct, and • Choosing arguments and defending positions in situations of conflicting interests. The seminar will use current issues, such as dilemmas in the life sciences or bio fuels to demonstrate the problematic relationship between science and politics. The seminar, however, does not focus on providing in-depth knowledge of these current issues. We strongly discourage students that have participated in an “Ethics for Engineers” seminar to take this course, because the contents of the two seminars overlap. Issues will be introduced by short presentations and a Q&A session, followed by group work on selected problems. All participants will have to prepare a presentation. Those requiring a graded certificate (“Schein”) additionally have to write a 3-4 page paper on selected issues. The seminar will use interactive tools of teaching such as role playing and simulations. Group work and active participation is expected at all stages of the seminar. |
Literature |
will be announced in lecture wird im Seminar bekannt gegeben |
Course L1734: Projectrealisation: TUHH goes circular - Sustainability in Research, Education and campus management |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | |
Lecturer | Prof. Kerstin Kuchta |
Language | EN |
Cycle |
WiSe/ |
Content | |
Literature |
Wird im Seminar bekanntgegeben Will be announced in lecture. |
Course L1872: Social Learning: Social Commitment in Refugee Issues / Master |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Schriftliche Ausarbeitung |
Examination duration and scale | 10 Seiten |
Lecturer | Muthana Al-Temimi |
Language | DE |
Cycle |
WiSe/ |
Content | folgt |
Literature |
Wird im Seminar bekannt gegeben. Will be announced in lecture. |
Course L1647: Soft skill seminar for dual study programme (dual@TUHH) / Master |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | Referat mit 2-3 Videoübungen à 20 Minuten + anschließende Diskussion |
Lecturer | Silke Wolckenhaar-Wagner, Dr. Henning Haschke |
Language | DE |
Cycle |
WiSe/ |
Content | |
Literature |
Course L1771: The Arabic Spring an its Consequences |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Dieter Bednarz |
Language | DE |
Cycle |
WiSe/ |
Content |
The world wide walkover of the internet dramatically changed the perception of classical media like newspapers, magazines and even TV. In this seminar the reasons of and the consequences for the dramatic changes regarding our information habits will be analyzed and discussed: Taking a close look at the Middle East the political impact of the new media´s triumphal procession will be assessed and evaluated. How come that Twitter and Facebook on one hand facilitated the so called Arabic Spring and caused hope for the rise of democracy in the region, while on the other hand the revolutionaries failed so dramatically - at least for now. Keeping a close eye on both fields, the Media and the Middle East, the seminar will discuss the standards of ethics in politics and journalism. |
Literature |
Wird im Seminar angegeben und besprochen. Will be announced in the lecture. |
Course L1916: Responsible Conduct in Technology & Science |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Dr. Mirko Himmel, Dr. Ines Krohn-Molt |
Language | DE |
Cycle |
WiSe/ |
Content |
Aim of the seminar is raising awareness for the responsibility of engineers and researchers for a proper and ethical conduct in technology and science. The Participants will present and discuss practical examples for good as well as bad conduct in science.
|
Literature | folgt im Seminar |
Course L1991: What can philosophy do? |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Dr. Ursula Töller |
Language | DE |
Cycle |
WiSe/ |
Content |
Over the centuries, the philosophy is lined up as a discipline that provides complex and universal answers to contemporary history and circumstances. Often, she could design utopias that have led the way for political upheaval. While all scientific disciplines are subject to an increasing differentiation, the philosophy in the second half of the 20th century has lost its claim to universality. But what then are the topics of the philosophy of the 20th and 21st century and what impact have philosophical theories for processes of change? We will provide an overview of Western philosophies of the 20th and 21st century. and take a critical look at the self-understanding of philosophy. |
Literature |
Gerhardt Schweppenhäuser: Kritische Theorie, Stuttgart 2010 Postmoderne und Dekonstruktion, Texte französischer Philosophen der Gegenwart, hrsg. von Peter Engelmann, Reclam UB 8668 Thomas Rentsch: Philosophie des 20. Jhdts. Von Husserl bis Derrida, München 2014 Geschichte der Philosophie in Text und Darstellung, Bd. 8=20 Jhdt. Reclam UB 9918 Geschichte der Philosophie in Text und Darstellung, Bd. 9= Gegenwart Reclam UB 18267 |
Course L2343: Academic Writing and Presentation for Master-Students |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Referat |
Examination duration and scale | etwa 20 Minuten Präsentation und 10-20 Minuten Diskussion |
Lecturer | Dr. Ursula Töller |
Language | DE |
Cycle |
WiSe/ |
Content |
The course is aimed at Master students who are planning to write their thesis, want to pursue their PhD or intend to present their research results at conferences and in journals. The course is structured on three levels: 1. writing, 2. presenting and 3. interacting in organizational structures. The latter refers to the work environment at university as well as in research groups and enterprises. In the course of the seminar, the participants become acquainted with various methods and theories on the subject. Furthermore, the methods and theories will be put into practice, reflected upon and discussed as part of the seminar. |
Literature |
Tim McClintock: Dealing with Specific Types of Difficult People. (2008) |
Course L2029: “Lying press”? Functions and current challenges of journalism |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Examination Form | Mündliche Prüfung |
Examination duration and scale | 20 min |
Lecturer | Prof. Horst Pöttker |
Language | DE |
Cycle |
WiSe/ |
Content |
Lying press - there is a revival of the disparaging invective. Journalists use to shoot it down by leading it back to its supposed roots in the NS-propaganda. This is less convincing as several parties and ideologies have used it since the middle of the 19th century to discredit the media of other parties and ideologies. And it is missing the core of the problem. Critics are reasonably afraid that the choice of “lying press” to the “non-word of the year” 2014 has blocked the question, if there is a justified criticism of information media and journalism - or more precisely of the relationship between journalism and its audience. If this is the case both - journalism and audience - are involved from the perspective of inter actionism. Against this background interactive instructions will be given by scholarly literature and practical examples from the German and international media business. Questions like the following will be discussed:
Objective is solid learning about professional tasks, ethics, techniques, endagerments, history and current problems of journalism including science journalism. |
Literature |
Zur Einführung: Lilienthal, Volker/Neverla, Irene (Hrsg.) (2017): „Lügenpresse“. Anatomie eines politischen Kampfbegriffs. Köln: Kiepenheuer & Witsch. https://www.kiwi-verlag.de/buch/luegenpresse/978-3-462-31782-4/ Pöttker, Horst (2010): Der Beruf zur Öffentlichkeit. Über Aufgabe, Grundsätze und Perspektiven des Journalismus in der Mediengesellschaft aus der Sicht praktischer Vernunft. In: Publizistik, 55. Jg., H. 2, S. 107-128. https://www.springerprofessional.de/en/der-beruf-zur-oeffentlichkeit/5889108 Weischenberg, S. (2007): Das Jahrhundert des Journalismus ist vorbei. Rekonstruktionen und Prognosen zur Formation gesellschaftlicher Selbstbeobachtung. In: Bartelt-Kircher, G. et al.: Krise der Printmedien - eine Krise des Journalismus? Berlin und New York, de Gruyter Saur, S. 32-60. https://medien21.wordpress.com/2011/10/17/weischenberg-das-jahrhundert-des-journalismus-ist-vorbei/ Eine ausführliche Literaturliste wird am Anfang des Seminars verteilt. |
Module M0804: Research Project and Seminar |
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Courses | ||||||||||||
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Module Responsible | Prof. Karl-Heinz Zimmermann |
Admission Requirements | None |
Recommended Previous Knowledge | Basic knowledge and techniques in the chosen field of specialization. |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge | Students are able to acquire advanced knowledge in a specific field of Computer Science or a closely related subject. |
Skills | Students are able to work self-dependent in a field of Computer Science or a closely related field. |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Independent Study Time 372, Study Time in Lecture 168 |
Credit points | 18 |
Course achievement | None |
Examination | Study work |
Examination duration and scale | Presentation of a current research topic (25-30 min and 5 min discussion). |
Assignment for the Following Curricula |
Computer Science: Core Qualification: Compulsory Information and Communication Systems: Core Qualification: Compulsory |
Course L1761: Project Work |
Typ | Projection Course |
Hrs/wk | 10 |
CP | 15 |
Workload in Hours | Independent Study Time 310, Study Time in Lecture 140 |
Lecturer | Dozenten des SD E |
Language | DE/EN |
Cycle | WiSe |
Content |
Current research topics of the chosen specialization. |
Literature |
Aktuelle Literatur zu Forschungsthemen aus der gewählten Vertiefungsrichtung. |
Course L0817: Seminar |
Typ | Seminar |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Dozenten des SD E |
Language | DE/EN |
Cycle | WiSe |
Content |
|
Literature | Wird vom Veranstalter bekanntgegeben. |
Specialization Computer and Software Engineering
Module M0753: Software Verification |
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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 apply the major verification techniques in model checking and deductive verification. They explain in formal terms syntax and semantics of the underlying logics, and assess the expressivity of different logics as well as their limitations. They classify formal properties of software systems. They find flaws in formal arguments, arising from modeling artifacts or underspecification. |
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Skills |
Students formulate provable properties of a software system in a formal language. They develop logic-based models that properly abstract from the software under verification and, where necessary, adapt model or property. They construct proofs and property checks by hand or using tools for model checking or deductive verification, and reflect on the scope of the results. Presented with a verification problem in natural language, they select the appropriate verification technique and justify their choice. |
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Personal Competence | |||||||||
Social Competence |
Students discuss relevant topics in class. They defend their solutions orally. They communicate in English. |
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Autonomy |
Using accompanying on-line material for self study, students can assess their level of knowledge continuously and adjust it appropriately. Working on exercise problems, they receive additional feedback. Within limits, they can set their own learning goals. Upon successful completion, students can identify and precisely formulate new problems in academic or applied research in the field of software verification. Within this field, they can conduct independent studies to acquire the necessary competencies and compile their findings in academic reports. They can devise plans to arrive at new solutions or assess existing ones. |
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Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 | ||||||||
Credit points | 6 | ||||||||
Course achievement |
|
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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 I. Computer Science: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems: Compulsory International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory |
Course L0629: Software Verification |
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 | WiSe |
Content |
|
Literature |
|
Course L0630: Software Verification |
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 | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1270: Technical Complementary Course I for CSMS (according to Subject Specific Regulations) |
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Courses | ||||
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Module Responsible | Prof. Karl-Heinz Zimmermann |
Admission Requirements | None |
Recommended Previous Knowledge | None |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
The students acquire advanced knowledge in a technical subject available at TUHH. |
Skills |
The students acquire professional competence in a technical subject available at TUHH. |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Depends on choice of courses |
Credit points | 6 |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory |
Module M0667: Algorithmic Algebra |
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Courses | ||||||||||||
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Module Responsible | Dr. Prashant Batra |
Admission Requirements | None |
Recommended Previous Knowledge |
Mathe I-III (Real analysis,computing in Vector spaces , principle of complete induction) Diskrete Mathematik I (gropus, rings, ideals, fields; euclidean algorithm) |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students can discuss logical connections between the following concepts and explain them by means of examples: Smith normal form, Chinese remainder theorem, grid point sets, integer solution of inequality systems. |
Skills |
Students are able to access independently further logical connections between the concepts with which they have become familiar and are able to verify them. Students are able to develop a suitable solution approach to given problems, to pursue it and to evaluate the results critically, such as in solving multivariate equation systems and in grid point theory. |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory |
Course L0422: Algorithmic Algebra |
Typ | Lecture | ||||||||||||||
Hrs/wk | 3 | ||||||||||||||
CP | 5 | ||||||||||||||
Workload in Hours | Independent Study Time 108, Study Time in Lecture 42 | ||||||||||||||
Lecturer | Dr. Prashant Batra | ||||||||||||||
Language | DE | ||||||||||||||
Cycle | WiSe | ||||||||||||||
Content |
Extended euclidean algorithm, solution of the Bezout-equation Division with remainder (over rings) fast arithmetic algorithms (conversion, fast multiplications) discrete Fourier-transformation over rings Computation with modular remainders, solving of remainder systems (chinese remainder theorem), solvability of integer linear systems over the integers linearization of polynomial equations-- matrix approach Sylvester-matrix, elimination elimination in rings, elimination of many variables Buchberger algorithm, Gröbner basis Minkowskis Lattice Point theorem and integer-valued optimization LLL-algorithm for construction of 'short' lattice vectors in polynomial time |
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Literature |
von zur Gathen, Joachim; Gerhard, Jürgen Modern computer algebra. 3rd ed. (English) Zbl 1277.68002 Yap, Chee Keng Free download for students from author's website: http://cs.nyu.edu/yap/book/berlin/ Cox, David; Little, John; O’Shea, Donal eBook: http://dx.doi.org/10.1007/978-0-387-35651-8
Koepf, Wolfram springer eBook: http://dx.doi.org/10.1007/3-540-29895-9 Kaplan, Michael springer eBook: http://dx.doi.org/10.1007/b137968 |
Course L0423: Algorithmic Algebra |
Typ | Recitation Section (small) |
Hrs/wk | 1 |
CP | 1 |
Workload in Hours | Independent Study Time 16, Study Time in Lecture 14 |
Lecturer | Dr. Prashant Batra |
Language | DE |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0836: Communication Networks |
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Courses | ||||||||||||||||
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Module Responsible | Prof. Andreas Timm-Giel |
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 are able to describe the principles and structures of communication networks in detail. They can explain the formal description methods of communication networks and their protocols. They are able to explain how current and complex communication networks work and describe the current research in these examples. |
Skills |
Students are able to evaluate the performance of communication networks using the learned methods. They are able to work out problems themselves and apply the learned methods. They can apply what they have learned autonomously on further and new communication networks. |
Personal Competence | |
Social Competence |
Students are able to define tasks themselves in small teams and solve these problems together using the learned methods. They can present the obtained results. They are able to discuss and critically analyse the solutions. |
Autonomy |
Students are able to obtain the necessary expert knowledge for understanding the functionality and performance capabilities of new communication networks independently. |
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 |
Credit points | 6 |
Course achievement | None |
Examination | Presentation |
Examination duration and scale | 1.5 hours colloquium with three students, therefore about 30 min per student. Topics of the colloquium are the posters from the previous poster session and the topics of the module. |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory Aircraft Systems Engineering: Specialisation Avionic and Embedded Systems: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems: Elective Compulsory Mechatronics: Technical Complementary Course: Elective Compulsory Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory |
Course L0897: Analysis and Structure of Communication Networks |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Prof. Andreas Timm-Giel |
Language | EN |
Cycle | WiSe |
Content | |
Literature |
Further literature is announced at the beginning of the lecture. |
Course L0899: Selected Topics of Communication Networks |
Typ | Project-/problem-based Learning |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Prof. Andreas Timm-Giel |
Language | EN |
Cycle | WiSe |
Content | Example networks selected by the students will be researched on in a PBL course by the students in groups and will be presented in a poster session at the end of the term. |
Literature |
|
Course L0898: Communication Networks Excercise |
Typ | Project-/problem-based Learning |
Hrs/wk | 1 |
CP | 2 |
Workload in Hours | Independent Study Time 46, Study Time in Lecture 14 |
Lecturer | Prof. Andreas Timm-Giel |
Language | EN |
Cycle | WiSe |
Content | Part of the content of the lecture Communication Networks are reflected in computing tasks in groups, others are motivated and addressed in the form of a PBL exercise. |
Literature |
|
Module M0926: Distributed Algorithms |
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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 know the main abstractions of distributed algorithms (synchronous/asynchronous model, message passing and shared memory model). They are able to describe complexity measures for distributed algorithms (round , message and memory complexity). They explain well known distributed algorithms for important problems such as leader election, mutual exclusion, graph coloring, spanning trees. They know the fundamental techniques used for randomized algorithms. |
Skills | Students design their own distributed algorithms and analyze their complexity. They make use of known standard algorithms. They compute the complexity of randomized algorithms. |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 45 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory |
Course L1071: Distributed Algorithms |
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/EN |
Cycle | WiSe |
Content |
|
Literature |
|
Course L1072: Distributed Algorithms |
Typ | Recitation Section (large) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Volker Turau |
Language | DE/EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0586: Efficient Algorithms |
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Courses | ||||||||||||
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Module Responsible | Prof. Siegfried Rump |
Admission Requirements | None |
Recommended Previous Knowledge |
Programming in Matlab and/or C Basic knowledge in discrete mathematics |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
The students are able to explain the basic theory and methods of network algorithms and in particular their data structures. They are able to analyze the computational behavior and computing time of linear programming algorithms as well network algorithms. Moreover the students can distinguish between efficiently solvable and NP-hard problems. |
Skills |
The students are able to analyze complex tasks and can determine possibilities to transform them into networking algorithms. In particular they can efficiently implement basic algorithms and data structures of LP- and network algorithms and identify possible weaknesses. They are able to distinguish between different efficient data structures and are able to use them appropriately. |
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 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory |
Course L0120: Efficient Algorithms |
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 |
- Linear Programming - Data structures - Leftist heaps - Minimum spanning tree - Shortest path - Maximum flow - NP-hard problems via max-cut |
Literature |
R. E. Tarjan: Data Structures and Network Algorithms. CBMS 44, Society for Industrial and Applied Mathematics, Philadelphia, PA, 1983. Wesley, 2011 http://algs4.cs.princeton.edu/home/ V. Chvátal, ``Linear Programming'', Freeman, New York, 1983. |
Course L1207: Efficient Algorithms |
Typ | Recitation Section (small) |
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 M1271: Technical Complementary Course II for CSMS (according to Subject Specific Regulations) |
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Courses | ||||
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Module Responsible | Prof. Karl-Heinz Zimmermann |
Admission Requirements | None |
Recommended Previous Knowledge | None |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Die Studierenden können die wesentlichen Inhalte des technischen Faches im Rahmen eines Vortrages oder einer Diskussion wiedergeben. |
Skills |
The students acquire professional competence in a technical subject available at TUHH. |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Depends on choice of courses |
Credit points | 6 |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Intelligence Engineering: Elective Compulsory |
Module M1318: Wireless Sensor Networks |
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Courses | ||||||||||||||||
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Module Responsible | Prof. Bernd-Christian Renner |
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 110, Study Time in Lecture 70 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory Microelectronics and Microsystems: Specialisation Embedded Systems: Elective Compulsory |
Course L1815: Wireless Sensor Networks |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Prof. Bernd-Christian Renner |
Language | EN |
Cycle | SoSe |
Content | |
Literature |
Course L1816: Wireless Sensor Networks |
Typ | Recitation Section (small) |
Hrs/wk | 1 |
CP | 1 |
Workload in Hours | Independent Study Time 16, Study Time in Lecture 14 |
Lecturer | Prof. Bernd-Christian Renner |
Language | EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Course L1819: Wireless Sensor Networks: Project |
Typ | Project-/problem-based Learning |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Bernd-Christian Renner |
Language | EN |
Cycle | SoSe |
Content |
The PrBL course part will be performed in small groups of students. Topics are from the field of wireless sensor networks and are loosely related to the lecture contents. Project descriptions and goals are provided but have to be solved by the students as follow:
Throughout the semester, there will be meetings with the supervisor on a regular basis (weekly or biweekly). Details about the topics and course organization will be provided in the first lecture. Please note that the number of participants is limited due to the available capacity (rooms, equipment, supervisors). |
Literature |
Will be provided individually |
Module M0556: Computer Graphics |
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Courses | ||||||||||||
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Module Responsible | Prof. Tobias Knopp |
Admission Requirements | None |
Recommended Previous Knowledge |
Students are expected to have a solid knowledge of object-oriented programming as well as of linear algebra and geometry. |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students have acquired a theoretical basis in computer graphics and have a clear understanding of the process of computer animation. |
Skills |
Students have acquired
|
Personal Competence | |
Social Competence |
Students are trained in communicating abstract ideas and are familiar with planning and conducting projects within a small team. |
Autonomy |
Students are able to direct complex computer animation projects. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory |
Course L0145: Computer Graphics |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Tobias Knopp |
Language | EN |
Cycle | SoSe |
Content |
Computer graphics and animation are leading to an unprecedented visual revolution. The course deals with its technological foundations:
Students will be be working on a series of mini-projects which will eventually evolve into a final project. Learning computer graphics and animation resembles learning a musical instrument. Therefore, doing your projects well and in time is essential for performing well on this course. |
Literature |
Alan H. Watt: 3D Computer Graphics. Harlow: Pearson (3rd ed., repr., 2009). Dariush Derakhshani: Introducing Autodesk Maya 2014. New York, NY : Wiley (2013). |
Course L0768: Computer Graphics |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Tobias Knopp |
Language | EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1248: Compilers for Embedded Systems |
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Courses | ||||||||||||
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Module Responsible | Prof. Heiko Falk |
Admission Requirements | None |
Recommended Previous Knowledge |
Module "Embedded Systems" C/C++ Programming skills |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
The relevance of embedded systems increases from year to year. Within such systems, the amount of software to be executed on embedded processors grows continuously due to its lower costs and higher flexibility. Because of the particular application areas of embedded systems, highly optimized and application-specific processors are deployed. Such highly specialized processors impose high demands on compilers which have to generate code of highest quality. After the successful attendance of this course, the students are able
The high demands on compilers for embedded systems make effective code optimizations mandatory. The students learn in particular,
Since compilers for embedded systems often have to optimize for multiple objectives (e.g., average- or worst-case execution time, energy dissipation, code size), the students learn to evaluate the influence of optimizations on these different criteria. |
Skills |
After successful completion of the course, students shall be able to translate high-level program code into machine code. They will be enabled to assess which kind of code optimization should be applied most effectively at which abstraction level (e.g., source or assembly code) within a compiler. While attending the labs, the students will learn to implement a fully functional compiler including optimizations. |
Personal Competence | |
Social Competence |
Students are able to solve similar problems alone or in a group and to present the results accordingly. |
Autonomy |
Students are able to acquire new knowledge from specific literature and to associate this knowledge with other classes. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Mechatronics: Specialisation System Design: Elective Compulsory Mechatronics: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory |
Course L1692: Compilers for 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 | DE/EN |
Cycle | SoSe |
Content |
|
Literature |
|
Course L1693: Compilers for Embedded Systems |
Typ | Project-/problem-based Learning |
Hrs/wk | 1 |
CP | 2 |
Workload in Hours | Independent Study Time 46, Study Time in Lecture 14 |
Lecturer | Prof. Heiko Falk |
Language | DE/EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0837: Simulation of Communication Networks |
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Courses | ||||||||
|
Module Responsible | Prof. Andreas Timm-Giel |
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 explain the necessary stochastics, the discrete event simulation technology and modelling of networks for performance evaluation. |
Skills |
Students are able to apply the method of simulation for performance evaluation to different, also not practiced, problems of communication networks. The students can analyse the obtained results and explain the effects observed in the network. They are able to question their own results. |
Personal Competence | |
Social Competence |
Students are able to acquire expert knowledge in groups, present the results, and discuss solution approaches and results. They are able to work out solutions for new problems in small teams. |
Autonomy |
Students are able to transfer independently and in discussion with others the acquired method and expert knowledge to new problems. They can identify missing knowledge and acquire this knowledge independently. |
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory Aircraft Systems Engineering: Specialisation Avionic and Embedded Systems: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory |
Course L0887: Simulation of Communication Networks |
Typ | Project-/problem-based Learning |
Hrs/wk | 5 |
CP | 6 |
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 |
Lecturer | Prof. Andreas Timm-Giel |
Language | EN |
Cycle | SoSe |
Content |
In the course necessary basic stochastics and the discrete event simulation are introduced. Also simulation models for communication networks, for example, traffic models, mobility models and radio channel models are presented in the lecture. Students work with a simulation tool, where they can directly try out the acquired skills, algorithms and models. At the end of the course increasingly complex networks and protocols are considered and their performance is determined by simulation. |
Literature |
Further literature is announced at the beginning of the lecture. |
Module M0924: Software for Embedded 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 know the basic principles and procedures of software engineering for embedded systems. They are able to describe the usage and pros of event based programming using interrupts. They know the components and functions of a concrete microcontroller. The participants explain requirements of real time systems. They know at least three scheduling algorithms for real time operating systems including their pros and cons. |
Skills | Students build interrupt-based programs for a concrete microcontroller. They build and use a preemptive scheduler. They use peripheral components (timer, ADC, EEPROM) to realize complex tasks for embedded systems. To interface with external components they utilize serial protocols. |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory Mechatronics: Technical Complementary Course: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Mechatronics: Specialisation System Design: Elective Compulsory |
Course L1069: Software for Embdedded 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/EN |
Cycle | SoSe |
Content |
|
Literature |
|
Course L1070: Software for Embdedded Systems |
Typ | Recitation Section (small) |
Hrs/wk | 3 |
CP | 3 |
Workload in Hours | Independent Study Time 48, Study Time in Lecture 42 |
Lecturer | Prof. Volker Turau |
Language | DE/EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1301: Software Testing |
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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 different phases of testing, describe fundamental techniques of different types of testing, and paraphrase the basic principles of the corresponding test process. They give examples of software development scenarios and the corresponding test type and technique. They explain algorithms used for particular testing techniques and describe possible advantages and limitations. |
Skills |
Students identify the appropriate testing type and technique for a given problem. They adapt and execute respective algorithms to execute a concrete test technique properly. They interpret testing results and execute corresponding steps for proper re-test scenarios. They write and analyze test specifications. They apply bug finding techniques for non-trivial problems. |
Personal Competence | |
Social Competence |
Students discuss relevant topics in class. They defend their solutions orally. |
Autonomy |
Students can assess their level of knowledge continuously and adjust it appropriately, based on feedback and on self-guided studies. Within limits, they can set their own learning goals. Upon successful completion, students can identify and precisely formulate new problems in academic or applied research in the field of software testing. Within this field, they can conduct independent studies to acquire the necessary competencies and compile their findings in academic reports. They can devise plans to arrive at new solutions or assess existing ones |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Subject theoretical and practical work |
Examination duration and scale | Software |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory |
Course L1791: Software Testing |
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 |
|
Course L1792: Software Testing |
Typ | Project-/problem-based Learning |
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 |
|
Module M0711: Numerical Mathematics II |
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Courses | ||||||||||||
|
Module Responsible | Prof. Sabine Le Borne |
Admission Requirements | None |
Recommended Previous Knowledge |
|
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students are able to
|
Skills |
Students are able to
|
Personal Competence | |
Social Competence |
Students are able to
|
Autonomy |
Students are capable
|
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 25 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation III. Mathematics: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory |
Course L0568: Numerical Mathematics II |
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. Jens-Peter Zemke |
Language | DE/EN |
Cycle | SoSe |
Content |
|
Literature |
|
Course L0569: Numerical Mathematics II |
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. Jens-Peter Zemke |
Language | DE/EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1397: Model Checking - Proof Engines and Algorithms |
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Courses | ||||||||||||
|
Module Responsible | Prof. Görschwin Fey |
Admission Requirements | None |
Recommended Previous Knowledge | Basic knowledge about data structures and algorithms |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students know
|
Skills |
Students can
|
Personal Competence | |
Social Competence |
Students
|
Autonomy | Using accompanying material students independently learn in-depth relations between concepts explained in the lecture and additional solution strategies. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Software: Elective Compulsory |
Course L1979: Model Checking - Proof Engines and Algorithms |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Görschwin Fey |
Language | DE/EN |
Cycle | SoSe |
Content |
Correctness is a major concern in embedded systems. Model checking can fully automatically proof formal properties about digital hardware or software. Such properties are given in temporal logic, e.g., to prove "No two orthogonal traffic lights will ever be green." And how do the underlying reasoning algorithms work so effectively in practice despite a computational complexity of NP hardness and beyond?
But what are the limitations of model checking? Among other topics, the lecture will consider the following topics:
|
Literature |
Edmund M. Clarke, Jr., Orna Grumberg, and Doron A. Peled. 1999. Model Checking. MIT Press, Cambridge, MA, USA. A. Biere, A. Biere, M. Heule, H. van Maaren, and T. Walsh. 2009. Handbook of Satisfiability: Volume 185 Frontiers in Artificial Intelligence and Applications. IOS Press, Amsterdam, The Netherlands, The Netherlands. Selected research papers |
Course L1980: Model Checking - Proof Engines and Algorithms |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Görschwin Fey |
Language | DE/EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1405: Randomised Algorithms and Random Graphs |
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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 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation III. Mathematics: Elective Compulsory Mathematical Modelling in Engineering: Theory, Numerics, Applications: Specialisation l. Numerics (TUHH): Elective Compulsory |
Course L2010: Randomised Algorithms and Random Graphs |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Anusch Taraz, Prof. Volker Turau |
Language | DE/EN |
Cycle | SoSe |
Content |
Randomized Algorithms:
|
Literature |
|
Course L2011: Randomised Algorithms and Random Graphs |
Typ | Recitation Section (large) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Anusch Taraz, Prof. Volker Turau |
Language | DE/EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0758: Application Security |
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Courses | ||||||||||||
|
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 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 120 minutes |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: 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 |
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 M1400: Design of Dependable Systems |
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Courses | ||||||||||||
|
Module Responsible | Prof. Görschwin Fey | ||||||||
Admission Requirements | None | ||||||||
Recommended Previous Knowledge | Basic knowledge about data structures and algorithms | ||||||||
Educational Objectives | After taking part successfully, students have reached the following learning results | ||||||||
Professional Competence | |||||||||
Knowledge |
In the following "dependable" summarizes the concepts Reliability, Availability, Maintainability, Safety and Security. Knowledge about approaches for designing dependable systems, e.g.,
Knowledge about methods for the analysis of dependable systems |
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Skills |
Ability to implement dependable systems using the above approaches. Ability to analyzs the dependability of systems using the above methods for analysis. |
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Personal Competence | |||||||||
Social Competence |
Students
|
||||||||
Autonomy | Using accompanying material students independently learn in-depth relations between concepts explained in the lecture and additional solution strategies. | ||||||||
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 | ||||||||
Credit points | 6 | ||||||||
Course achievement |
|
||||||||
Examination | Oral exam | ||||||||
Examination duration and scale | 30 min | ||||||||
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation I. Computer Science: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems: Elective Compulsory Mechatronics: Specialisation System Design: Elective Compulsory Microelectronics and Microsystems: Specialisation Embedded Systems: Elective Compulsory |
Course L2000: Designing Dependable Systems |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Görschwin Fey |
Language | DE/EN |
Cycle | SoSe |
Content |
Description The term dependability comprises various aspects of a system. These are typically:
Contents The module introduces the basic concepts for the design and the analysis of dependable systems. Design examples for getting practical hands-on-experience in dependable design techniques. The module focuses towards embedded systems. The following topics are covered:
|
Literature |
Course L2001: Designing Dependable Systems |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Görschwin Fey |
Language | DE/EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1337: Curves, Cryptosystems and Quantum Computing |
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Courses | ||||||||
|
Module Responsible | Prof. Karl-Heinz Zimmermann |
Admission Requirements | None |
Recommended Previous Knowledge |
Higher algebra, linear algebra, and mathematical analysis. |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge | The students understand the basic theory of elliptic curves, classical cryptosysteme, basic methods of cryptanalysis, cryptography of elliptic curves, quantum computing and the post-quantum computing scenario, algebraic codes over curves, and the famous theorem of Riemann-Roch. |
Skills | The students are in the position to apply the group law of elliptic curves, to find out if a curve is non-singular, to sketch cryptographic algorithms that make use of elliptic curves, to specify quantum algorithms, and to determine the parameters of algebraic codes defined over curves. |
Personal Competence | |
Social Competence |
Students are able to solve specific problems alone or in a group and to present the results accordingly. |
Autonomy |
Students are able to acquire new knowledge from specific standard books and to associate the acquired knowledge to other classes. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 25 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory |
Course L1870: Curves, Cryptosystems and Quantum Computing |
Typ | Lecture |
Hrs/wk | 4 |
CP | 6 |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Lecturer | Prof. Karl-Heinz Zimmermann |
Language | DE/EN |
Cycle | SoSe |
Content | |
Literature |
Module M0839: Traffic Engineering |
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Courses | ||||||||||||||||
|
Module Responsible | Prof. Andreas Timm-Giel |
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 describe methods for planning, optimisation and performance evaluation of communication networks. |
Skills |
Students are able to solve typical planning and optimisation tasks for communication networks. Furthermore they are able to evaluate the network performance using queuing theory. Students are able to apply independently what they have learned to other and new problems. They can present their results in front of experts and discuss them. |
Personal Competence | |
Social Competence | |
Autonomy |
Students are able to acquire the necessary expert knowledge to understand the functionality and performance of new communication networks independently. |
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory |
Course L0902: Seminar Traffic Engineering |
Typ | Seminar |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Prof. Andreas Timm-Giel, Dr. Phuong Nga Tran |
Language | EN |
Cycle | WiSe |
Content | Selected applications of methods for planning, optimization, and performance evaluation of communication networks, which have been introduced in the traffic engineering lecture are prepared by the students and presented in a seminar. |
Literature |
|
Course L0900: Traffic Engineering |
Typ | Lecture |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Prof. Andreas Timm-Giel, Dr. Phuong Nga Tran |
Language | EN |
Cycle | WiSe |
Content |
Network Planning and Optimization |
Literature |
Literatur: |
Course L0901: Traffic Engineering Exercises |
Typ | Recitation Section (small) |
Hrs/wk | 1 |
CP | 2 |
Workload in Hours | Independent Study Time 46, Study Time in Lecture 14 |
Lecturer | Prof. Andreas Timm-Giel |
Language | EN |
Cycle | WiSe |
Content |
Accompanying exercise for the traffic engineering course |
Literature |
Literatur: |
Module M0910: Advanced System-on-Chip Design (Lab) |
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Courses | ||||||||
|
Module Responsible | Prof. Heiko Falk |
Admission Requirements | None |
Recommended Previous Knowledge |
Successful completion of the practical FPGA lab of module "Computer Architecture" is a mandatory prerequisite. |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
This module provides in-depth, hands-on experience on advanced concepts of computer architecture. Using the Hardware Description Language VHDL and using reconfigurable FPGA hardware boards, students learn how to design complex computer systems (so-called systems-on-chip, SoCs), that are commonly found in the domain of embedded systems, in actual hardware. Starting with a simple processor architecture, the students learn to how realize instruction-processing of a computer processor according to the principle of pipelining. They implement different styles of cache-based memory hierarchies, examine strategies for dynamic scheduling of machine instructions and for branch prediction, and finally construct a complex MPSoC system (multi-processor system-on-chip) that consists of multiple processor cores that are connected via a shared bus. |
Skills |
Students will be able to analyze, how highly specific and individual computer systems can be constructed using a library of given standard components. They evaluate the interferences between the physical structure of a computer system and the software executed thereon. This way, they will be enabled to estimate the effects of design decision at the hardware level on the performance of the entire system, to evaluate the whole and complex system and to propose design options to improve a system. |
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, to transform this knowledge into actual implementations of complex hardware structures, and to associate this knowledge with contents of other classes. |
Workload in Hours | Independent Study Time 138, Study Time in Lecture 42 |
Credit points | 6 |
Course achievement | None |
Examination | Subject theoretical and practical work |
Examination duration and scale | VHDL Codes and FPGA-based implementations |
Assignment for the Following Curricula |
Computer Science: Specialisation I. Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Microelectronics and Microsystems: Specialisation Embedded Systems: Elective Compulsory Microelectronics and Microsystems: Specialisation Embedded Systems: Elective Compulsory |
Course L1061: Advanced System-on-Chip Design |
Typ | Project-/problem-based Learning |
Hrs/wk | 3 |
CP | 6 |
Workload in Hours | Independent Study Time 138, Study Time in Lecture 42 |
Lecturer | Prof. Heiko Falk |
Language | DE/EN |
Cycle | WiSe |
Content |
|
Literature |
|
Specialization Intelligence Engineering
Module M1270: Technical Complementary Course I for CSMS (according to Subject Specific Regulations) |
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Courses | ||||
|
Module Responsible | Prof. Karl-Heinz Zimmermann |
Admission Requirements | None |
Recommended Previous Knowledge | None |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
The students acquire advanced knowledge in a technical subject available at TUHH. |
Skills |
The students acquire professional competence in a technical subject available at TUHH. |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Depends on choice of courses |
Credit points | 6 |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory |
Module M0550: Digital Image Analysis |
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Courses | ||||||||
|
Module Responsible | Prof. Rolf-Rainer Grigat |
Admission Requirements | None |
Recommended Previous Knowledge |
System theory of one-dimensional signals (convolution and correlation, sampling theory, interpolation and decimation, Fourier transform, linear time-invariant systems), linear algebra (Eigenvalue decomposition, SVD), basic stochastics and statistics (expectation values, influence of sample size, correlation and covariance, normal distribution and its parameters), basics of Matlab, basics in optics |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students can
|
Skills |
Students are able to
Students can solve simple arithmetical problems relating to the specification and design of image processing and image analysis systems. Students are able to assess different solution approaches in multidimensional decision-making areas. Students can undertake a prototypical analysis of processes in Matlab. |
Personal Competence | |
Social Competence |
k.A. |
Autonomy |
Students can solve image analysis tasks independently using the relevant literature. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 60 Minutes, Content of Lecture and materials in StudIP |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory Electrical Engineering: Specialisation Medical Technology: Elective Compulsory Electrical Engineering: Specialisation Medical Technology: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory |
Course L0126: Digital Image Analysis |
Typ | Lecture |
Hrs/wk | 4 |
CP | 6 |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Lecturer | Prof. Rolf-Rainer Grigat |
Language | EN |
Cycle | WiSe |
Content |
|
Literature |
Bredies/Lorenz, Mathematische Bildverarbeitung, Vieweg, 2011 |
Module M0677: Digital Signal Processing and Digital Filters |
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Courses | ||||||||||||
|
Module Responsible | Prof. Gerhard Bauch |
Admission Requirements | None |
Recommended Previous Knowledge |
|
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge | The students know and understand basic algorithms of digital signal processing. They are familiar with the spectral transforms of discrete-time signals and are able to describe and analyse signals and systems in time and image domain. They know basic structures of digital filters and can identify and assess important properties including stability. They are aware of the effects caused by quantization of filter coefficients and signals. They are familiar with the basics of adaptive filters. They can perform traditional and parametric methods of spectrum estimation, also taking a limited observation window into account. |
Skills | The students are able to apply methods of digital signal processing to new problems. They can choose and parameterize suitable filter striuctures. In particular, the can design adaptive filters according to the minimum mean squared error (MMSE) criterion and develop an efficient implementation, e.g. based on the LMS or RLS algorithm. Furthermore, the students are able to apply methods of spectrum estimation and to take the effects of a limited observation window into account. |
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 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory Computational Science and Engineering: Specialisation II. Engineering Science: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory |
Course L0446: Digital Signal Processing and Digital Filters |
Typ | Lecture |
Hrs/wk | 3 |
CP | 4 |
Workload in Hours | Independent Study Time 78, Study Time in Lecture 42 |
Lecturer | Prof. Gerhard Bauch |
Language | EN |
Cycle | WiSe |
Content |
|
Literature |
K.-D. Kammeyer, K. Kroschel: Digitale Signalverarbeitung. Vieweg Teubner. V. Oppenheim, R. W. Schafer, J. R. Buck: Zeitdiskrete Signalverarbeitung. Pearson StudiumA. V. W. Hess: Digitale Filter. Teubner. Oppenheim, R. W. Schafer: Digital signal processing. Prentice Hall. S. Haykin: Adaptive flter theory. L. B. Jackson: Digital filters and signal processing. Kluwer. T.W. Parks, C.S. Burrus: Digital filter design. Wiley. |
Course L0447: Digital Signal Processing and Digital Filters |
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 | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0563: Robotics |
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Courses | ||||||||||||
|
Module Responsible | Prof. Uwe Weltin |
Admission Requirements | None |
Recommended Previous Knowledge |
Fundamentals of electrical engineering Broad knowledge of mechanics Fundamentals of control theory |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge | Students are able to describe fundamental properties of robots and solution approaches for multiple problems in robotics. |
Skills |
Students are able to derive and solve equations of motion for various manipulators. Students can generate trajectories in various coordinate systems. Students can design linear and partially nonlinear controllers for robotic manipulators. |
Personal Competence | |
Social Competence | Students are able to work goal-oriented in small mixed groups. |
Autonomy |
Students are able to recognize and improve knowledge deficits independently. With instructor assistance, students are able to evaluate their own knowledge level and define a further course of study. |
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 120 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Aircraft Systems Engineering: Specialisation Aircraft Systems: Elective Compulsory International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory International Management and Engineering: Specialisation II. Product Development and Production: Elective Compulsory Mechanical Engineering and Management: Core Qualification: Compulsory Mechatronics: Core Qualification: Compulsory Product Development, Materials and Production: Specialisation Product Development: Elective Compulsory Product Development, Materials and Production: Specialisation Production: Elective Compulsory Product Development, Materials and Production: Specialisation Materials: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Product Development and Production: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory |
Course L0168: Robotics: Modelling and Control |
Typ | Lecture |
Hrs/wk | 3 |
CP | 3 |
Workload in Hours | Independent Study Time 48, Study Time in Lecture 42 |
Lecturer | Prof. Uwe Weltin |
Language | EN |
Cycle | WiSe |
Content |
Fundamental kinematics of rigid body systems Newton-Euler equations for manipulators Trajectory generation Linear and nonlinear control of robots |
Literature |
Craig, John J.: Introduction to Robotics Mechanics and Control, Third Edition, Prentice Hall. ISBN 0201-54361-3 |
Course L1305: Robotics: Modelling and Control |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Uwe Weltin |
Language | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0633: Industrial Process Automation |
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Courses | ||||||||||||
|
Module Responsible | Prof. Alexander Schlaefer | ||||||||
Admission Requirements | None | ||||||||
Recommended Previous Knowledge |
mathematics and optimization methods |
||||||||
Educational Objectives | After taking part successfully, students have reached the following learning results | ||||||||
Professional Competence | |||||||||
Knowledge |
The students can evaluate and assess discrete event systems. They can evaluate properties of processes and explain methods for process analysis. The students can compare methods for process modelling and select an appropriate method for actual problems. They can discuss scheduling methods in the context of actual problems and give a detailed explanation of advantages and disadvantages of different programming methods. The students can relate process automation to methods from robotics and sensor systems as well as to recent topics like 'cyberphysical systems' and 'industry 4.0'. |
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Skills |
The students are able to develop and model processes and evaluate them accordingly. This involves taking into account optimal scheduling, understanding algorithmic complexity, and implementation using PLCs. |
||||||||
Personal Competence | |||||||||
Social Competence |
The students work in teams to solve problems. |
||||||||
Autonomy |
The students can reflect their knowledge and document the results of their work. |
||||||||
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 | ||||||||
Credit points | 6 | ||||||||
Course achievement |
|
||||||||
Examination | Written exam | ||||||||
Examination duration and scale | 90 minutes | ||||||||
Assignment for the Following Curricula |
Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory Chemical and Bioprocess Engineering: Specialisation Chemical Process Engineering: Elective Compulsory Chemical and Bioprocess Engineering: Specialisation General Process Engineering: Elective Compulsory Chemical and Bioprocess Engineering: Specialisation Chemical Process Engineering: Elective Compulsory Chemical and Bioprocess Engineering: Specialisation General Process Engineering: Elective Compulsory Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory Aircraft Systems Engineering: Specialisation Cabin Systems: Elective Compulsory Aircraft Systems Engineering: Specialisation Cabin Systems: Elective Compulsory International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory Process Engineering: Specialisation Process Engineering: Elective Compulsory Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory Process Engineering: Specialisation Process Engineering: Elective Compulsory |
Course L0344: Industrial Process Automation |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Alexander Schlaefer |
Language | EN |
Cycle | WiSe |
Content |
- foundations of problem solving and system modeling, discrete event systems |
Literature |
J. Lunze: „Automatisierungstechnik“, Oldenbourg Verlag, 2012 |
Course L0345: Industrial Process Automation |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Alexander Schlaefer |
Language | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0549: Scientific Computing and Accuracy |
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Courses | ||||||||||||
|
Module Responsible | Prof. Siegfried Rump |
Admission Requirements | None |
Recommended Previous Knowledge |
Basic knowledge in numerics |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
The students have deeper knowledge of numerical and semi-numerical methods with the goal to compute principally exact and accurate error bounds. For several fundamental problems they know algorithms with the verification of the correctness of the computed result. |
Skills |
The students can devise algorithms for several basic problems which compute rigorous error bounds for the solution and analyze the sensitivity with respect to variation of the input data as well. |
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 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory Computational Science and Engineering: Specialisation Scientific Computing: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Process Engineering: Specialisation Process Engineering: Elective Compulsory Process Engineering: Specialisation Chemical Process Engineering: Elective Compulsory |
Course L0122: Verification Methods |
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 |
|
Literature |
Neumaier: Interval Methods for Systems of Equations. In: Encyclopedia of Mathematics and its Applications. Cambridge University Press, 1990 S.M. Rump. Verification methods: Rigorous results using floating-point arithmetic. Acta Numerica, 19:287-449, 2010. |
Course L1208: Verification Methods |
Typ | Recitation Section (small) |
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 M0623: Intelligent Systems in Medicine |
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Courses | ||||||||||||||||
|
Module Responsible | Prof. Alexander Schlaefer | ||||||||||||
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 analyze and solve clinical treatment planning and decision support problems using methods for search, optimization, and planning. They are able to explain methods for classification and their respective advantages and disadvantages in clinical contexts. The students can compare different methods for representing medical knowledge. They can evaluate methods in the context of clinical data and explain challenges due to the clinical nature of the data and its acquisition and due to privacy and safety requirements. |
||||||||||||
Skills |
The students can give reasons for selecting and adapting methods for classification, regression, and prediction. They can assess the methods based on actual patient data and evaluate the implemented methods. |
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Personal Competence | |||||||||||||
Social Competence |
The students discuss the results of other groups, provide helpful feedback and can incoorporate feedback into their work. |
||||||||||||
Autonomy |
The students can reflect their knowledge and document the results of their work. They can present the results in an appropriate manner. |
||||||||||||
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 | ||||||||||||
Credit points | 6 | ||||||||||||
Course achievement |
|
||||||||||||
Examination | Written exam | ||||||||||||
Examination duration and scale | 90 minutes | ||||||||||||
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Medical Technology: Elective Compulsory Computational Science and Engineering: Specialisation Systems Engineering and Robotics: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: 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 Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory |
Course L0331: Intelligent Systems in Medicine |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Alexander Schlaefer |
Language | EN |
Cycle | WiSe |
Content |
- methods for search, optimization, planning, classification, regression and prediction in a clinical context |
Literature |
Russel & Norvig: Artificial Intelligence: a Modern Approach, 2012 |
Course L0334: Intelligent Systems in Medicine |
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 | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Course L0333: Intelligent Systems in Medicine |
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 | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0676: Digital Communications |
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Courses | ||||||||||||||||
|
Module Responsible | Prof. Gerhard Bauch | ||||||||
Admission Requirements | None | ||||||||
Recommended Previous Knowledge |
|
||||||||
Educational Objectives | After taking part successfully, students have reached the following learning results | ||||||||
Professional Competence | |||||||||
Knowledge | The students are able to understand, compare and design modern digital information transmission schemes. They are familiar with the properties of linear and non-linear digital modulation methods. They can describe distortions caused by transmission channels and design and evaluate detectors including channel estimation and equalization. They know the principles of single carrier transmission and multi-carrier transmission as well as the fundamentals of basic multiple access schemes. | ||||||||
Skills | The students are able to design and analyse a digital information transmission scheme including multiple access. They are able to choose a digital modulation scheme taking into account transmission rate, required bandwidth, error probability, and further signal properties. They can design an appropriate detector including channel estimation and equalization taking into account performance and complexity properties of suboptimum solutions. They are able to set parameters of a single carrier or multi carrier transmission scheme and trade the properties of both approaches against each other. | ||||||||
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 | ||||||||
Course achievement |
|
||||||||
Examination | Written exam | ||||||||
Examination duration and scale | 90 min | ||||||||
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Core Qualification: Compulsory Computational Science and Engineering: Specialisation II. Engineering Science: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems: Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Networks: Elective Compulsory International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory |
Course L0444: Digital Communications |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Gerhard Bauch |
Language | DE/EN |
Cycle | WiSe |
Content |
|
Literature |
K. Kammeyer: Nachrichtenübertragung, Teubner P.A. Höher: Grundlagen der digitalen Informationsübertragung, Teubner. J.G. Proakis, M. Salehi: Digital Communications. McGraw-Hill. S. Haykin: Communication Systems. Wiley R.G. Gallager: Principles of Digital Communication. Cambridge A. Goldsmith: Wireless Communication. Cambridge. D. Tse, P. Viswanath: Fundamentals of Wireless Communication. Cambridge. |
Course L0445: Digital Communications |
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 |
Course L0646: Laboratory Digital Communications |
Typ | Practical Course |
Hrs/wk | 1 |
CP | 1 |
Workload in Hours | Independent Study Time 16, Study Time in Lecture 14 |
Lecturer | Prof. Gerhard Bauch |
Language | DE/EN |
Cycle | WiSe |
Content |
- DSL transmission - Random processes - Digital data transmission |
Literature |
K. Kammeyer: Nachrichtenübertragung, Teubner P.A. Höher: Grundlagen der digitalen Informationsübertragung, Teubner. J.G. Proakis, M. Salehi: Digital Communications. McGraw-Hill. S. Haykin: Communication Systems. Wiley R.G. Gallager: Principles of Digital Communication. Cambridge A. Goldsmith: Wireless Communication. Cambridge. D. Tse, P. Viswanath: Fundamentals of Wireless Communication. Cambridge. |
Module M0846: Control Systems Theory and Design |
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Courses | ||||||||||||
|
Module Responsible | Prof. Herbert Werner |
Admission Requirements | None |
Recommended Previous Knowledge | Introduction to Control Systems |
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 on specific problems to arrive at joint solutions. |
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 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 120 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Core Qualification: Compulsory Energy Systems: Core Qualification: Elective Compulsory Aircraft Systems Engineering: Specialisation Aircraft Systems: Compulsory Aircraft Systems Engineering: Specialisation Avionic and Embedded Systems: Elective Compulsory Computational Science and Engineering: Specialisation II. Engineering Science: Elective Compulsory International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory Mechatronics: Core Qualification: 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: Compulsory Biomedical Engineering: Specialisation Management and Business Administration: Elective Compulsory Product Development, Materials and Production: Core Qualification: Elective Compulsory Theoretical Mechanical Engineering: Core Qualification: Compulsory |
Course L0656: Control Systems Theory and Design |
Typ | Lecture |
Hrs/wk | 2 |
CP | 4 |
Workload in Hours | Independent Study Time 92, Study Time in Lecture 28 |
Lecturer | Prof. Herbert Werner |
Language | EN |
Cycle | WiSe |
Content |
State space methods (single-input single-output) • State space models and transfer functions, state feedback Digital Control System identification and model order reduction Case study |
Literature |
|
Course L0657: Control Systems Theory and Design |
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 | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0881: Mathematical Image Processing |
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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 are able to
|
Skills |
Students are able to
|
Personal Competence | |
Social Competence |
Students are able to work together in heterogeneously composed teams (i.e., teams from different study programs and background knowledge) and to explain theoretical foundations. |
Autonomy |
|
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 20 min |
Assignment for the Following Curricula |
Bioprocess Engineering: Specialisation A - General Bioprocess Engineering: Elective Compulsory Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Modeling and Simulation: Elective Compulsory Computational Science and Engineering: Specialisation III. Mathematics: Elective Compulsory Mechatronics: Technical Complementary Course: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Process Engineering: Specialisation Process Engineering: Elective Compulsory |
Course L0991: Mathematical Image Processing |
Typ | Lecture |
Hrs/wk | 3 |
CP | 4 |
Workload in Hours | Independent Study Time 78, Study Time in Lecture 42 |
Lecturer | Prof. Marko Lindner, Dr. Christian Seifert |
Language | DE/EN |
Cycle | WiSe |
Content |
|
Literature | Bredies/Lorenz: Mathematische Bildverarbeitung |
Course L0992: Mathematical Image Processing |
Typ | Recitation Section (small) |
Hrs/wk | 1 |
CP | 2 |
Workload in Hours | Independent Study Time 46, Study Time in Lecture 14 |
Lecturer | Prof. Marko Lindner |
Language | DE/EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0629: Intelligent Autonomous Agents and Cognitive Robotics |
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Courses | ||||||||||||
|
Module Responsible | Rainer Marrone |
Admission Requirements | None |
Recommended Previous Knowledge | Vectors, matrices, Calculus |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students can explain the agent abstraction, define intelligence in terms of rational behavior, and give details about agent design (goals, utilities, environments). They can describe the main features of environments. The notion of adversarial agent cooperation can be discussed in terms of decision problems and algorithms for solving these problems. For dealing with uncertainty in real-world scenarios, students can summarize how Bayesian networks can be employed as a knowledge representation and reasoning formalism in static and dynamic settings. In addition, students can define decision making procedures in simple and sequential settings, with and with complete access to the state of the environment. In this context, students can describe techniques for solving (partially observable) Markov decision problems, and they can recall techniques for measuring the value of information. Students can identify techniques for simultaneous localization and mapping, and can explain planning techniques for achieving desired states. Students can explain coordination problems and decision making in a multi-agent setting in term of different types of equilibria, social choice functions, voting protocol, and mechanism design techniques. |
Skills |
Students can select an appropriate agent architecture for concrete agent application scenarios. For simplified agent application students can derive decision trees and apply basic optimization techniques. For those applications they can also create Bayesian networks/dynamic Bayesian networks and apply bayesian reasoning for simple queries. Students can also name and apply different sampling techniques for simplified agent scenarios. For simple and complex decision making students can compute the best action or policies for concrete settings. In multi-agent situations students will apply techniques for finding different equilibria states,e.g., Nash equilibria. For multi-agent decision making students will apply different voting protocols and compare and explain the results. |
Personal Competence | |
Social Competence |
Students are able to discuss their solutions to problems with others. They communicate in English |
Autonomy |
Students are able of checking their understanding of complex concepts by solving varaints of concrete problems |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 90 minutes |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory Mechatronics: Technical Complementary Course: 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 Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory |
Course L0341: Intelligent Autonomous Agents and Cognitive Robotics |
Typ | Lecture |
Hrs/wk | 2 |
CP | 4 |
Workload in Hours | Independent Study Time 92, Study Time in Lecture 28 |
Lecturer | Rainer Marrone |
Language | EN |
Cycle | WiSe |
Content |
|
Literature |
|
Course L0512: Intelligent Autonomous Agents and Cognitive Robotics |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Rainer Marrone |
Language | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1336: Soft Computing - Introduction to Machine Learning |
||||||||
Courses | ||||||||
|
Module Responsible | Prof. Karl-Heinz Zimmermann |
Admission Requirements | None |
Recommended Previous Knowledge |
Bachelor in Computer Science. Basics in higher mathematics are inevitable, like calculus, linear algebra, graph theory, and optimization. |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students are able to formalize, compute, and analyze belief networks, alignments of sequences, hidden Markov models, phylogenetic tree models, neural networks, and fuzzy controllers. In particular, inference and learning in belief networks are important topics that the students should be able to master. |
Skills | Students can apply the relevant algorithms and determine their complexity, and they can make use of the statistics language R. |
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 to other fields. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 25 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory |
Course L1869: Soft Computing |
Typ | Lecture |
Hrs/wk | 4 |
CP | 6 |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Lecturer | Prof. Karl-Heinz Zimmermann, Dr. Mehwish Saleemi |
Language | DE/EN |
Cycle | WiSe |
Content |
Students are able to formalize, compute, and analyze belief
networks, alignments of sequences, hidden Markov models, phylogenetic
tree models, neural networks, and fuzzy controllers. In particular,
inference and learning in belief networks are important
topics that the students should be able to master. Students can apply the relevant algorithms and determine their complexity, and they can make use of the statistics language R. |
Literature |
1. David Barber, Bayes Reasoning and Machine Learning, Cambridge Univ. Press, Cambridge, 2012. |
Module M1271: Technical Complementary Course II for CSMS (according to Subject Specific Regulations) |
||||
Courses | ||||
|
Module Responsible | Prof. Karl-Heinz Zimmermann |
Admission Requirements | None |
Recommended Previous Knowledge | None |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Die Studierenden können die wesentlichen Inhalte des technischen Faches im Rahmen eines Vortrages oder einer Diskussion wiedergeben. |
Skills |
The students acquire professional competence in a technical subject available at TUHH. |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Depends on choice of courses |
Credit points | 6 |
Assignment for the Following Curricula |
Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computer Science: Specialisation Intelligence Engineering: Elective Compulsory |
Module M1302: Applied Humanoid Robotics |
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Courses | ||||||||
|
Module Responsible | Patrick Göttsch |
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 96, Study Time in Lecture 84 |
Credit points | 6 |
Course achievement | None |
Examination | Written elaboration |
Examination duration and scale | 5-10 pages |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory |
Course L1794: Applied Humanoid Robotics |
Typ | Project-/problem-based Learning |
Hrs/wk | 6 |
CP | 6 |
Workload in Hours | Independent Study Time 96, Study Time in Lecture 84 |
Lecturer | Patrick Göttsch |
Language | DE/EN |
Cycle |
WiSe/ |
Content |
|
Literature |
|
Module M0551: Pattern Recognition and Data Compression |
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Courses | ||||||||
|
Module Responsible | Prof. Rolf-Rainer Grigat |
Admission Requirements | None |
Recommended Previous Knowledge |
Linear algebra (including PCA, unitary transforms), stochastics and statistics, binary arithmetics |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students can name the basic concepts of pattern recognition and data compression. Students are able to discuss logical connections between the concepts covered in the course and to explain them by means of examples. |
Skills |
Students can apply statistical methods to classification problems in pattern recognition and to prediction in data compression. On a sound theoretical and methodical basis they can analyze characteristic value assignments and classifications and describe data compression and video signal coding. They are able to use highly sophisticated methods and processes of the subject area. Students are capable of assessing different solution approaches in multidimensional decision-making areas. |
Personal Competence | |
Social Competence |
k.A. |
Autonomy |
Students are capable of identifying problems independently and of solving them scientifically, using the methods they have learnt. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 60 Minutes, Content of Lecture and materials in StudIP |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Mechatronics: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory |
Course L0128: Pattern Recognition and Data Compression |
Typ | Lecture |
Hrs/wk | 4 |
CP | 6 |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Lecturer | Prof. Rolf-Rainer Grigat |
Language | EN |
Cycle | SoSe |
Content |
Structure of a pattern recognition system, statistical decision theory, classification based on statistical models, polynomial regression, dimension reduction, multilayer perceptron regression, radial basis functions, support vector machines, unsupervised learning and clustering, algorithm-independent machine learning, mixture models and EM, adaptive basis function models and boosting, Markov random fields Information, entropy, redundancy, mutual information, Markov processes, basic coding schemes (code length, run length coding, prefix-free codes), entropy coding (Huffman, arithmetic coding), dictionary coding (LZ77/Deflate/LZMA2, LZ78/LZW), prediction, DPCM, CALIC, quantization (scalar and vector quantization), transform coding, prediction, decorrelation (DPCM, DCT, hybrid DCT, JPEG, JPEG-LS), motion estimation, subband coding, wavelets, HEVC (H.265,MPEG-H) |
Literature |
Schürmann: Pattern Classification, Wiley 1996 Salomon, Data Compression, the Complete Reference, Springer, 2000 |
Module M0630: Robotics and Navigation in Medicine |
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Courses | ||||||||||||||||
|
Module Responsible | Prof. Alexander Schlaefer | ||||||||||||
Admission Requirements | None | ||||||||||||
Recommended Previous Knowledge |
|
||||||||||||
Educational Objectives | After taking part successfully, students have reached the following learning results | ||||||||||||
Professional Competence | |||||||||||||
Knowledge |
The students can explain kinematics and tracking systems in clinical contexts and illustrate systems and their components in detail. Systems can be evaluated with respect to collision detection and safety and regulations. Students can assess typical systems regarding design and limitations. |
||||||||||||
Skills |
The students are able to design and evaluate navigation systems and robotic systems for medical applications. |
||||||||||||
Personal Competence | |||||||||||||
Social Competence |
The students discuss the results of other groups, provide helpful feedback and can incoorporate feedback into their work. |
||||||||||||
Autonomy |
The students can reflect their knowledge and document the results of their work. They can present the results in an appropriate manner. |
||||||||||||
Workload in Hours | Independent Study Time 110, Study Time in Lecture 70 | ||||||||||||
Credit points | 6 | ||||||||||||
Course achievement |
|
||||||||||||
Examination | Written exam | ||||||||||||
Examination duration and scale | 90 minutes | ||||||||||||
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Medical Technology: Elective Compulsory International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: 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 Product Development, Materials and Production: Specialisation Product Development: Elective Compulsory Product Development, Materials and Production: Specialisation Production: Elective Compulsory Product Development, Materials and Production: Specialisation Materials: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory |
Course L0335: Robotics and Navigation in Medicine |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Alexander Schlaefer |
Language | EN |
Cycle | SoSe |
Content |
- kinematics |
Literature |
Spong et al.: Robot Modeling and Control, 2005 |
Course L0338: Robotics and Navigation in Medicine |
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 | EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Course L0336: Robotics and Navigation in Medicine |
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 | EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0673: Information Theory and Coding |
||||||||||||
Courses | ||||||||||||
|
Module Responsible | Prof. Gerhard Bauch |
Admission Requirements | None |
Recommended Previous Knowledge |
|
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge | The students know the basic definitions for quantification of information in the sense of information theory. They know Shannon's source coding theorem and channel coding theorem and are able to determine theoretical limits of data compression and error-free data transmission over noisy channels. They understand the principles of source coding as well as error-detecting and error-correcting channel coding. They are familiar with the principles of decoding, in particular with modern methods of iterative decoding. They know fundamental coding schemes, their properties and decoding algorithms. |
Skills | The students are able to determine the limits of data compression as well as of data transmission through noisy channels and based on those limits to design basic parameters of a transmission scheme. They can estimate the parameters of an error-detecting or error-correcting channel coding scheme for achieving certain performance targets. They are able to compare the properties of basic channel coding and decoding schemes regarding error correction capabilities, decoding delay, decoding complexity and to decide for a suitable method. They are capable of implementing basic coding and decoding schemes in software. |
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 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory Computational Science and Engineering: Specialisation II. Engineering Science: Elective Compulsory Information and Communication Systems: Core Qualification: Compulsory International Management and Engineering: Specialisation II. Electrical Engineering: Elective Compulsory Mechatronics: Technical Complementary Course: Elective Compulsory |
Course L0436: Information Theory and Coding |
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 |
Bossert, M.: Kanalcodierung. Oldenbourg. Friedrichs, B.: Kanalcodierung. Springer. Lin, S., Costello, D.: Error Control Coding. Prentice Hall. Roth, R.: Introduction to Coding Theory. Johnson, S.: Iterative Error Correction. Cambridge. Richardson, T., Urbanke, R.: Modern Coding Theory. Cambridge University Press. Gallager, R. G.: Information theory and reliable communication. Whiley-VCH Cover, T., Thomas, J.: Elements of information theory. Wiley. |
Course L0438: Information Theory and Coding |
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 M1310: Discrete Differential Geometry |
||||||||
Courses | ||||||||
|
Module Responsible | Prof. Karl-Heinz Zimmermann |
Admission Requirements | None |
Recommended Previous Knowledge |
Linear Algebra, Multivariate Calculus |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
These lectures are on geometrical aspects of the solutions of differential equations and their treatment on the computer. The required basics from linear algebra and analysis are reviewed at the beginning. Applications are to curved surfaces in space, to mechanics and mechatronics, to different types of field equations, and to the tranfer of mathematical constructions to data types, compiler functions, programming languages, and special compute circuits. - basic prerequisites from linear algebra, tensors, exterior algebra, Clifford algebras - basic prerequisites from coordinate-free analysis, vector fields and differential forms, integration, discretization - local differential geometry: connections, symplectic geometry and Hamiltonian systems, Riemannian geometry, discretization - global differential geometry: manifolds, Lie groups, fiber bundles, random processes, space and time |
Skills | |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 25 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory |
Course L1808: Discrete Differential Geometry |
Typ | Lecture |
Hrs/wk | 4 |
CP | 6 |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Lecturer | Prof. Georg Friedrich Mayer-Lindenberg |
Language | DE/EN |
Cycle | SoSe |
Content |
These lectures deal with geometric aspects of differential equations and with their treatment on the computer. The prerequisites from linear algebra and analysis are reviewed at the beginning. Applications are to curved surfaces, to classical mechanics and mechatronics, to various field equations, to computer graphics and to transferring mathematical constructions to data types, compiler functions, programming languages, and special hardware. Keywords: Basics from linear algebra, tensors, exterior algebra, Clifford algebras, tuple types Basics of coordinate-free analysis, vector fields and differential forms, integration, discrete exterior calculus Local differential geometry: connections, symplectic geometry, Riemannian geometry, discrete mechanics and connections Global differential geometry: manifolds, Lie groups, fibre bundles, Fourier decompositions, random processes, space and time |
Literature |
Agricola, Friedrich, Vektoranalysis, Vieweg/Teubner 2010 A.C. Da Silva, Lectures on Symplectic Geometry, Springer L.N. Math. 1764 J. Snygg, Differential Geometry using Clifford's Algebra, Birkhäuser 2010 T. Frankel, The Geometry of Physics, Cambridge U. P. 2012 M.Desbrun et al., Discrete exterior calculus, arXiv:math/0508341v2 J.Marsden et al., Discrete Mechanics and Variational Integrators, Acta numerica. 2001 |
Module M0711: Numerical Mathematics II |
||||||||||||
Courses | ||||||||||||
|
Module Responsible | Prof. Sabine Le Borne |
Admission Requirements | None |
Recommended Previous Knowledge |
|
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Students are able to
|
Skills |
Students are able to
|
Personal Competence | |
Social Competence |
Students are able to
|
Autonomy |
Students are capable
|
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 25 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Computer Science: Specialisation Computer and Software Engineering: Elective Compulsory Computational Science and Engineering: Specialisation III. Mathematics: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory |
Course L0568: Numerical Mathematics II |
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. Jens-Peter Zemke |
Language | DE/EN |
Cycle | SoSe |
Content |
|
Literature |
|
Course L0569: Numerical Mathematics II |
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. Jens-Peter Zemke |
Language | DE/EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0840: Optimal and Robust Control |
||||||||||||
Courses | ||||||||||||
|
Module Responsible | Prof. Herbert Werner |
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 | Students can work in small groups on specific problems to arrive at joint solutions. |
Autonomy |
Students are able to find required information in sources provided (lecture notes, literature, software documentation) and use it to solve given problems. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory Energy Systems: Core Qualification: Elective Compulsory Aircraft Systems Engineering: Specialisation Aircraft Systems: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Mechatronics: Specialisation System Design: 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 Product Development, Materials and Production: Specialisation Product Development: Elective Compulsory Product Development, Materials and Production: Specialisation Production: Elective Compulsory Product Development, Materials and Production: Specialisation Materials: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Core Qualification: Elective Compulsory |
Course L0658: Optimal and Robust Control |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Herbert Werner |
Language | EN |
Cycle | SoSe |
Content |
|
Literature |
|
Course L0659: Optimal and Robust Control |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Herbert Werner |
Language | EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0627: Machine Learning and Data Mining |
||||||||||||
Courses | ||||||||||||
|
Module Responsible | NN |
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 difference between instance-based and model-based learning approaches, and they can enumerate basic machine learning technique for each of the two basic approaches, either on the basis of static data, or on the basis of incrementally incoming data . For dealing with uncertainty, students can describe suitable representation formalisms, and they explain how axioms, features, parameters, or structures used in these formalisms can be learned automatically with different algorithms. Students are also able to sketch different clustering techniques. They depict how the performance of learned classifiers can be improved by ensemble learning, and they can summarize how this influences computational learning theory. Algorithms for reinforcement learning can also be explained by students. |
Skills |
Student derive decision trees and, in turn, propositional rule sets from simple and static data tables and are able to name and explain basic optimization techniques. They present and apply the basic idea of first-order inductive leaning. Students apply the BME, MAP, ML, and EM algorithms for learning parameters of Bayesian networks and compare the different algorithms. They also know how to carry out Gaussian mixture learning. They can contrast kNN classifiers, neural networks, and support vector machines, and name their basic application areas and algorithmic properties. Students can describe basic clustering techniques and explain the basic components of those techniques. Students compare related machine learning techniques, e.g., k-means clustering and nearest neighbor classification. They can distinguish various ensemble learning techniques and compare the different goals of those techniques. |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 90 minutes |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory International Management and Engineering: Specialisation II. Information Technology: Elective Compulsory Mechatronics: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory |
Course L0340: Machine Learning and Data Mining |
Typ | Lecture |
Hrs/wk | 2 |
CP | 4 |
Workload in Hours | Independent Study Time 92, Study Time in Lecture 28 |
Lecturer | Rainer Marrone |
Language | EN |
Cycle | SoSe |
Content |
|
Literature |
|
Course L0510: Machine Learning and Data Mining |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 2 |
Workload in Hours | Independent Study Time 32, Study Time in Lecture 28 |
Lecturer | Rainer Marrone |
Language | EN |
Cycle | SoSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0832: Advanced Topics in Control |
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Courses | ||||||||||||
|
Module Responsible | Prof. Herbert Werner |
Admission Requirements | None |
Recommended Previous Knowledge | H-infinity optimal control, mixed-sensitivity design, linear matrix inequalities |
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 and arrive at joint results. |
Autonomy |
Students are able to find required information in sources provided (lecture notes, literature, software documentation) and use it to solve given problems. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 30 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Control and Power Systems Engineering: Elective Compulsory Aircraft Systems Engineering: Specialisation Aircraft Systems: Elective Compulsory Aircraft Systems Engineering: Specialisation Avionic Systems: Elective Compulsory International Management and Engineering: Specialisation II. Mechatronics: Elective Compulsory Mechatronics: Specialisation System Design: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: 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 Biomedical Engineering: Specialisation Artificial Organs and Regenerative Medicine: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Core Qualification: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Robotics and Computer Science: Elective Compulsory |
Course L0661: Advanced Topics in Control |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Herbert Werner |
Language | EN |
Cycle | WiSe |
Content |
|
Literature |
|
Course L0662: Advanced Topics in Control |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Herbert Werner |
Language | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0552: 3D Computer Vision |
||||||||||||
Courses | ||||||||||||
|
Module Responsible | Prof. Rolf-Rainer Grigat |
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 and describe the field of projective geometry. |
Skills |
Students are capable of
With assistance from the teacher students are able to link the contents of the three subject areas (modules)
in practical assignments. |
Personal Competence | |
Social Competence |
Students can collaborate in a small team on the practical realization and testing of a system to reconstruct a three-dimensional scene or to evaluate volume data sets. |
Autonomy |
Students are able to solve simple tasks independently with reference to the contents of the lectures and the exercise sets. Students are able to solve detailed problems independently with the aid of the tutorial’s programming task. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 60 Minutes, Content of Lecture and materials in StudIP |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Computer Science: Specialisation II: Intelligence Engineering: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory Mechanical Engineering and Management: Specialisation Mechatronics: Elective Compulsory Mechatronics: Specialisation Intelligent Systems and Robotics: Elective Compulsory Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Robotics and Computer Science: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Numerics and Computer Science: Elective Compulsory |
Course L0129: 3D Computer Vision |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Rolf-Rainer Grigat |
Language | EN |
Cycle | WiSe |
Content |
|
Literature |
|
Course L0130: 3D Computer Vision |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Rolf-Rainer Grigat |
Language | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1552: Mathematics of Neural Networks |
||||||||||||
Courses | ||||||||||||
|
Module Responsible | Dr. Jens-Peter Zemke |
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 name, state and classify state-of-the-art neural networks and their corresponding mathematical basics. They can assess the difficulties of different neural networks. |
Skills | Students are able to implement, understand, and, tailored to the field of application, apply neural networks. |
Personal Competence | |
Social Competence |
Students can
|
Autonomy |
Students are able to
|
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Oral exam |
Examination duration and scale | 25 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Computer Science: Specialisation III. Mathematics: Elective Compulsory Computational Science and Engineering: Specialisation III. Mathematics: Elective Compulsory Technomathematics: Specialisation I. Mathematics: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Robotics and Computer Science: Elective Compulsory |
Course L2322: Mathematics of Neural Networks |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Dr. Jens-Peter Zemke |
Language | DE/EN |
Cycle | WiSe |
Content |
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Literature |
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Course L2323: Mathematics of Neural Networks |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Dr. Jens-Peter Zemke |
Language | DE/EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M0738: Digital Audio Signal Processing |
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Courses | ||||||||||||
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Module Responsible | Prof. Udo Zölzer |
Admission Requirements | None |
Recommended Previous Knowledge |
Signals and Systems |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
Die Studierenden können die grundlegenden Verfahren und Methoden der digitalen Audiosignalverarbeitung erklären. Sie können die wesentlichen physikalischen Effekte bei der Sprach- und Audiosignalverarbeitung erläutern und in Kategorien einordnen. Sie können einen Überblick der numerischen Methoden und messtechnischen Charakterisierung von Algorithmen zur Audiosignalverarbeitung geben. Sie können die erarbeiteten Algorithmen auf weitere Anwendungen im Bereich der Informationstechnik und Informatik abstrahieren. |
Skills |
The students will be able to apply methods and techniques from audio signal processing in the fields of mobile and internet communication. They can rely on elementary algorithms of audio signal processing in form of Matlab code and interactive JAVA applets. They can study parameter modifications and evaluate the influence on human perception and technical applications in a variety of applications beyond audio signal processing. Students can perform measurements in time and frequency domain in order to give objective and subjective quality measures with respect to the methods and applications. |
Personal Competence | |
Social Competence |
The students can work in small groups to study special tasks and problems and will be enforced to present their results with adequate methods during the exercise. |
Autonomy |
The students will be able to retrieve information out of the relevant literature in the field and putt hem into the context of the lecture. They can relate their gathered knowledge and relate them to other lectures (signals and systems, digital communication systems, image and video processing, and pattern recognition). They will be prepared to understand and communicate problems and effects in the field audio signal processing. |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 45 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Information and Communication Systems: Elective Compulsory Information and Communication Systems: Specialisation Secure and Dependable IT Systems, Focus Software and Signal Processing: Elective Compulsory Information and Communication Systems: Specialisation Communication Systems, Focus Signal Processing: Elective Compulsory Microelectronics and Microsystems: Specialisation Communication and Signal Processing: Elective Compulsory |
Course L0650: Digital Audio Signal Processing |
Typ | Lecture |
Hrs/wk | 3 |
CP | 4 |
Workload in Hours | Independent Study Time 78, Study Time in Lecture 42 |
Lecturer | Prof. Udo Zölzer |
Language | EN |
Cycle | WiSe |
Content |
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Literature |
- U. Zölzer, Digitale Audiosignalverarbeitung, 3. Aufl., B.G. Teubner, 2005. - U. Zölzer, Digitale Audio Signal Processing, 2nd Edition, J. Wiley & Sons, 2005. - U. Zölzer (Ed), Digital Audio Effects, 2nd Edition, J. Wiley & Sons, 2011.
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Course L0651: Digital Audio Signal Processing |
Typ | Recitation Section (large) |
Hrs/wk | 1 |
CP | 2 |
Workload in Hours | Independent Study Time 46, Study Time in Lecture 14 |
Lecturer | Prof. Udo Zölzer |
Language | EN |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Module M1249: Medical Imaging |
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Courses | ||||||||||||
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Module Responsible | Prof. Tobias Knopp |
Admission Requirements | None |
Recommended Previous Knowledge | |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge | |
Skills | |
Personal Competence | |
Social Competence | |
Autonomy | |
Workload in Hours | Independent Study Time 124, Study Time in Lecture 56 |
Credit points | 6 |
Course achievement | None |
Examination | Written exam |
Examination duration and scale | 90 min |
Assignment for the Following Curricula |
Computer Science: Specialisation Intelligence Engineering: Elective Compulsory Computer Science: Specialisation II: Intelligence Engineering: Elective Compulsory Electrical Engineering: Specialisation Medical Technology: Elective Compulsory Electrical Engineering: Specialisation Medical Technology: Elective Compulsory Theoretical Mechanical Engineering: Specialisation Bio- and Medical Technology: Elective Compulsory Theoretical Mechanical Engineering: Technical Complementary Course: Elective Compulsory |
Course L1694: Medical Imaging |
Typ | Lecture |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Tobias Knopp |
Language | DE |
Cycle | WiSe |
Content | |
Literature |
Bildgebende Verfahren in der Medizin; O. Dössel; Springer, Berlin, 2000 Bildgebende Systeme für die medizinische Diagnostik; H. Morneburg (Hrsg.); Publicis MCD, München, 1995 Introduction to the Mathematics of Medical Imaging; C. L.Epstein; Siam, Philadelphia, 2008 Medical Image Processing, Reconstruction and Restoration; J. Jan; Taylor and Francis, Boca Raton, 2006 Principles of Magnetic Resonance Imaging; Z.-P. Liang and P. C. Lauterbur; IEEE Press, New York, 1999 |
Course L1695: Medical Imaging |
Typ | Recitation Section (small) |
Hrs/wk | 2 |
CP | 3 |
Workload in Hours | Independent Study Time 62, Study Time in Lecture 28 |
Lecturer | Prof. Tobias Knopp |
Language | DE |
Cycle | WiSe |
Content | See interlocking course |
Literature | See interlocking course |
Thesis
Module M-002: Master Thesis |
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Courses | ||||
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Module Responsible | Professoren der TUHH |
Admission Requirements |
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Recommended Previous Knowledge | |
Educational Objectives | After taking part successfully, students have reached the following learning results |
Professional Competence | |
Knowledge |
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Skills |
The students are able:
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Personal Competence | |
Social Competence |
Students can
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Autonomy |
Students are able:
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Workload in Hours | Independent Study Time 900, Study Time in Lecture 0 |
Credit points | 30 |
Course achievement | None |
Examination | Thesis |
Examination duration and scale | According to General Regulations |
Assignment for the Following Curricula |
Civil Engineering: Thesis: Compulsory Bioprocess Engineering: Thesis: Compulsory Chemical and Bioprocess Engineering: Thesis: Compulsory Computer Science: Thesis: Compulsory Electrical Engineering: Thesis: Compulsory Energy and Environmental Engineering: Thesis: Compulsory Energy Systems: Thesis: Compulsory Environmental Engineering: Thesis: Compulsory Aircraft Systems Engineering: Thesis: Compulsory Global Innovation Management: Thesis: Compulsory Computational Science and Engineering: Thesis: Compulsory Information and Communication Systems: Thesis: Compulsory International Management and Engineering: Thesis: Compulsory Joint European Master in Environmental Studies - Cities and Sustainability: Thesis: Compulsory Logistics, Infrastructure and Mobility: Thesis: Compulsory Materials Science: Thesis: Compulsory Mathematical Modelling in Engineering: Theory, Numerics, Applications: Thesis: Compulsory Mechanical Engineering and Management: Thesis: Compulsory Mechatronics: Thesis: Compulsory Biomedical Engineering: Thesis: Compulsory Microelectronics and Microsystems: Thesis: Compulsory Product Development, Materials and Production: Thesis: Compulsory Renewable Energies: Thesis: Compulsory Naval Architecture and Ocean Engineering: Thesis: Compulsory Ship and Offshore Technology: Thesis: Compulsory Teilstudiengang Lehramt Metalltechnik: Thesis: Compulsory Theoretical Mechanical Engineering: Thesis: Compulsory Process Engineering: Thesis: Compulsory Water and Environmental Engineering: Thesis: Compulsory Certification in Engineering & Advisory in Aviation: Thesis: Compulsory |