Suchergebnis: Katalogdaten im Herbstsemester 2020

Elektrotechnik und Informationstechnologie Master Information
Master-Studium (Studienreglement 2018)
Signal Processing and Machine Learning
The core courses and specialisation courses below are a selection for students who wish to specialise in the area of "Signal Processing and Machine Learning ", see Link.

The individual study plan is subject to the tutor's approval.
Vertiefungsfächer
These specialisation courses are particularly recommended for the area of "Signal Processing and Machine Learning", but you are free to choose courses from any other field in agreement with your tutor.

A minimum of 40 credits must be obtained from specialisation courses during the MSc EEIT.
NummerTitelTypECTSUmfangDozierende
227-0477-00LAcoustics IW6 KP4GK. Heutschi
KurzbeschreibungIntroduction to the fundamentals of acoustics in the area of sound field calculations, measurement of acoustical events, outdoor sound propagation and room acoustics of large and small enclosures.
LernzielIntroduction to acoustics. Understanding of basic acoustical mechanisms. Survey of the technical literature. Illustration of measurement techniques in the laboratory.
InhaltFundamentals of acoustics, measuring and analyzing of acoustical events, anatomy and properties of the ear. Outdoor sound propagation, absorption and transmission of sound, room acoustics of large and small enclosures, architectural acoustics, noise and noise control, calculation of sound fields.
Skriptyes
263-5210-00LProbabilistic Artificial Intelligence Information Belegung eingeschränkt - Details anzeigen W8 KP3V + 2U + 2AA. Krause
KurzbeschreibungThis course introduces core modeling techniques and algorithms from machine learning, optimization and control for reasoning and decision making under uncertainty, and study applications in areas such as robotics and the Internet.
LernzielHow can we build systems that perform well in uncertain environments and unforeseen situations? How can we develop systems that exhibit "intelligent" behavior, without prescribing explicit rules? How can we build systems that learn from experience in order to improve their performance? We will study core modeling techniques and algorithms from statistics, optimization, planning, and control and study applications in areas such as sensor networks, robotics, and the Internet. The course is designed for graduate students.
InhaltTopics covered:
- Probability
- Probabilistic inference (variational inference, MCMC)
- Bayesian learning (Gaussian processes, Bayesian deep learning)
- Probabilistic planning (MDPs, POMPDPs)
- Multi-armed bandits and Bayesian optimization
- Reinforcement learning
Voraussetzungen / BesonderesSolid basic knowledge in statistics, algorithms and programming.
The material covered in the course "Introduction to Machine Learning" is considered as a prerequisite.
401-0647-00LIntroduction to Mathematical Optimization Belegung eingeschränkt - Details anzeigen W5 KP2V + 1UD. Adjiashvili
KurzbeschreibungIntroduction to basic techniques and problems in mathematical optimization, and their applications to a variety of problems in engineering.
LernzielThe goal of the course is to obtain a good understanding of some of the most fundamental mathematical optimization techniques used to solve linear programs and basic combinatorial optimization problems. The students will also practice applying the learned models to problems in engineering.
InhaltTopics covered in this course include:
- Linear programming (simplex method, duality theory, shadow prices, ...).
- Basic combinatorial optimization problems (spanning trees, shortest paths, network flows, ...).
- Modelling with mathematical optimization: applications of mathematical programming in engineering.
LiteraturInformation about relevant literature will be given in the lecture.
Voraussetzungen / BesonderesThis course is meant for students who did not already attend the course "Mathematical Optimization", which is a more advance lecture covering similar topics. Compared to "Mathematical Optimization", this course has a stronger focus on modeling and applications.
401-3054-14LProbabilistic Methods in Combinatorics Information W6 KP2V + 1UB. Sudakov
KurzbeschreibungThis course provides a gentle introduction to the Probabilistic Method, with an emphasis on methodology. We will try to illustrate the main ideas by showing the application of probabilistic reasoning to various combinatorial problems.
Lernziel
InhaltThe topics covered in the class will include (but are not limited to): linearity of expectation, the second moment method, the local lemma, correlation inequalities, martingales, large deviation inequalities, Janson and Talagrand inequalities and pseudo-randomness.
Literatur- The Probabilistic Method, by N. Alon and J. H. Spencer, 3rd Edition, Wiley, 2008.
- Random Graphs, by B. Bollobás, 2nd Edition, Cambridge University Press, 2001.
- Random Graphs, by S. Janson, T. Luczak and A. Rucinski, Wiley, 2000.
- Graph Coloring and the Probabilistic Method, by M. Molloy and B. Reed, Springer, 2002.
401-3621-00LFundamentals of Mathematical Statistics Information W10 KP4V + 1US. van de Geer
KurzbeschreibungThe course covers the basics of inferential statistics.
Lernziel
401-3901-00LMathematical OptimizationW11 KP4V + 2UR. Zenklusen
KurzbeschreibungMathematical treatment of diverse optimization techniques.
LernzielThe goal of this course is to get a thorough understanding of various classical mathematical optimization techniques with an emphasis on polyhedral approaches. In particular, we want students to develop a good understanding of some important problem classes in the field, of structural mathematical results linked to these problems, and of solution approaches based on this structural understanding.
InhaltKey topics include:
- Linear programming and polyhedra;
- Flows and cuts;
- Combinatorial optimization problems and techniques;
- Equivalence between optimization and separation;
- Brief introduction to Integer Programming.
Literatur- Bernhard Korte, Jens Vygen: Combinatorial Optimization. 6th edition, Springer, 2018.
- Alexander Schrijver: Combinatorial Optimization: Polyhedra and Efficiency. Springer, 2003. This work has 3 volumes.
- Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin. Network Flows: Theory, Algorithms, and Applications. Prentice Hall, 1993.
- Alexander Schrijver: Theory of Linear and Integer Programming. John Wiley, 1986.
Voraussetzungen / BesonderesSolid background in linear algebra.
401-4619-67LAdvanced Topics in Computational Statistics
Findet dieses Semester nicht statt.
W4 KP2Vkeine Angaben
KurzbeschreibungThis lecture covers selected advanced topics in computational statistics. This year the focus will be on graphical modelling.
LernzielStudents learn the theoretical foundations of the selected methods, as well as practical skills to apply these methods and to interpret their outcomes.
InhaltThe main focus will be on graphical models in various forms:
Markov properties of undirected graphs; Belief propagation; Hidden Markov Models; Structure estimation and parameter estimation; inference for high-dimensional data; causal graphical models
Voraussetzungen / BesonderesWe assume a solid background in mathematics, an introductory lecture in probability and statistics, and at least one more advanced course in statistics.
Wahlfächer
***more courses coming soon***

This is only a short selection. Other courses from the ETH course catalogue may be chosen in agreement with your tutor.

As an alternative to the elective courses, students may do a second semester project or an internship in industry. Please consult your tutor.
NummerTitelTypECTSUmfangDozierende
363-0511-00LManagerial Economics
Not for MSc students belonging to D-MTEC!
W4 KP3VP. Egger, M. Köthenbürger, N. Loumeau
Kurzbeschreibung"Managerial Economics" wendet Theorien und Methoden aus dem Bereich der Wirtschaftwissenschaften (Volks- und Betriebswirtschaftslehre) an, um das Entscheidungsverhalten von Unternehmen und Konsumenten im Kontext von Märkten zu analysieren. Der Kurs richtet sich an Studenten ohne wirtschaftswissenschaftliches Vorwissen.
LernzielZiel des Kurses ist es, in die Grundlagen des mikroökonomischen Denkens einzuführen. Aufbauend auf Prinzipien von Optimierung und Gleichgewicht stehen hierbei zentrale ökonomische Konzepte des Individual- und Firmenverhaltens und deren Interaktion in Entscheidungskontexten von Märkten im Mittelpunkt. Aus einer Analyse des Verhaltens einzelner Konsumenten und Produzenten werden wir die Nachfrage, das Angebot und Gleichgewichte von Märkten unter verschiedenen Annahmen zur vorherrschenden Marktstruktur (vollständiger Wettbewerb, Monopol, oligopolistische Marktformen) entwickeln und ökonomisch diskutieren. Die in diesem Kurs vermittelten Inhalte bilden eine wesentliche Grundlage für eine volks- und betriebswirtschaftliche Kompetenz mit Hinblick auf Entscheidungskontexte des privatwirtschaftlichen und öffentlichen Sektors.
Literatur"Mikroökonomie" von Robert Pindyck & Daniel Rubinfeld, aktualisierte 8. Auflage, 8/2013, (Pearson Studium - Economic VWL).
Voraussetzungen / BesonderesDer Kurs richtet sich sowohl an Bachelor als auch an Master Studenten. Es ist kein spezielles Vorwissen in den Bereichen Ökonomik und Management erforderlich.
351-0778-00LDiscovering Management
Entry level course in management for BSc, MSc and PHD students at all levels not belonging to D-MTEC. This course can be complemented with Discovering Management (Excercises) 351-0778-01.
W3 KP3GB. Clarysse, S. Brusoni, S. Feuerriegel, G. Grote, V. Hoffmann, T. Netland, G. von Krogh
KurzbeschreibungDiscovering Management offers an introduction to the field of business management and entrepreneurship for engineers and natural scientists. The module provides an overview of the principles of management, teaches knowledge about management that is highly complementary to the students' technical knowledge, and provides a basis for advancing the knowledge of the various subjects offered at D-MTEC.
LernzielDiscovering Management combines in an innovate format a set of theory lectures and a series of case studies. The learning model for Discovering Management involves 'learning by doing'. The objective is to introduce the students to the relevant topics of the management literature and give them a good introduction in entrepreneurship topics too. The course is a series of lectures on the topics of strategy, innovation, leadership, productions and operations management and corporate social responsibility. While the different theory lectures provide the theoretical and conceptual foundations, the experiential learning outcomes result from the case studies.
InhaltDiscovering Management aims to broaden the students' understanding of the principles of business management, emphasizing the interdependence of various topics in the development and management of a firm. The lectures introduce students not only to topics relevant for managing large corporations, but also touch upon the different aspects of starting up your own venture. The lectures will be presented by the respective area specialists at D-MTEC.
The course broadens the view and understanding of technology by linking it with its commercial applications and with society. The lectures are designed to introduce students to topics related to strategy, corporate innovation, leadership, value chain analysis, corporate social responsibility, and information management. Practical examples from case studies will stimulate the students to critically assess these issues.
Voraussetzungen / BesonderesDiscovering Management is designed to suit the needs and expectations of Bachelor students at all levels as well as Master and PhD students not belonging to D-MTEC. By providing an overview of Business Management, this course is an ideal enrichment of the standard curriculum at ETH Zurich.
No prior knowledge of business or economics is required to successfully complete this course.
351-0778-01LDiscovering Management (Exercises)
Complementary exercises for the module Discovering Managment.

Prerequisite: Participation and successful completion of the module Discovering Management (351-0778-00L) is mandatory.
W1 KP1UB. Clarysse, L. De Cuyper
KurzbeschreibungThis course is offered complementary to the basis course 351-0778-00L, "Discovering Management". The course offers additional exercises and case studies.
LernzielThis course is offered to complement the course 351-0778-00L. The course offers additional exercises and case studies.
InhaltThe course offers additional exercises and case studies concering:
Strategic Management; Technology and Innovation Management; Operations and Supply Chain Management; Finance and Accounting; Marketing and Sales.

Please refer to the course website for further information on the content, credit conditions and schedule of the module: Link
363-0790-00LTechnology Entrepreneurship Information W2 KP2VF. Hacklin
KurzbeschreibungThis course aims to equip future leaders with strategies, frameworks and tools for understanding, analyzing and building technology ventures. In so doing, this course lays particular emphasis on providing an overview of various technology-related dimensions of the entrepreneurial journey, including founding, financing and growing a venture.
Lernziel- Understand both the tension and link between entrepreneurship and technology
- Evaluate cases of success and failure in technology ventures
- Discuss a variety of approaches and frameworks for building and growing technology ventures
- Interact with entrepreneurial leaders and gain insight into their entrepreneurial journey
- Experiment with building blocks and tools for analyzing, structuring and prototyping technology ventures
InhaltMany industries are approaching, or find themselves in the midst of, dramatic structural changes. In many cases, such transformations are rooted in underlying technological shifts, such as digitization, nanoscale engineering, or 3D printing. Well known cases in point of affected sectors are in consumer electronics, media or manufacturing industries who are currently undergoing significant technology-driven disruptions. But also emerging shifts in the automotive sector or financial services give rise to severe questions of where and how the future value will be created and captured.
In a world characterized by disruption and change, technology ventures have taken a paramount role in significantly altering the global economic picture. As a consequence, there is a rising demand for complementing technological skills by entrepreneurial understanding.
Against this background, this course aims to equip future leaders with strategies, frameworks and tools for understanding, analyzing and building technology ventures. In so doing, this course lays particular emphasis on providing an overview of various technology-related dimensions of the entrepreneurial journey, including founding, financing and growing a venture.

See course website: Link
Skript- Lecture slides, cases and additional learning material provided during the course
363-1049-00LPrinciples of Conflict ResolutionW3 KP2VP. Grech
KurzbeschreibungThis course provides a transdisciplinary introduction to conflict resolution in international relations (primary focus), business and interpersonal relations.

Some time is devoted to analytic methods (non-cooperative game theory), making this course specifically suited for ETH students who are curious to apply their engineering/natural science background to a new domain.
LernzielRecognizing and understanding commonalities as well as differences between different conflict types, both structurally and topically.

Assessing different approaches to conflict analysis and resolution regarding their strengths and weaknesses.

Equilibrium computation in simple games.

Illustrating specific aspects of conflicts with real-life/historical examples.

Applying the presented theoretical approaches to real-life and stylized conflict situations in international relations, business and interpersonal relations.
InhaltTopics discussed:

1. Approaches to conflict analysis: international relations theory/political philosophy, (social) psychology, non-cooperative game theory, behavioral economics

2. Emphasis on strategic analysis: non-cooperative game theory (models for trust, commitment, brinkmanship, threats, promises etc.)

3. Conflictual negotiations: basic concepts, relationship building, dealing with non-cooperative counterparties, collaborative solution finding

4. Resolution methods with third-party intervention: mediation/conciliation, arbitration, adjudication, questions of implementation and enforcement (domestic measures, interstate measures: peacekeeping, peace enforcement, humanitarian interventions, sanctions etc.), conflict transformation: long-term measures for conflict resolution, peacebuilding.

Theoretical input will be amply illustrated by a variety of real-world examples in
-international relations (primary focus; e.g. wars, establishment of the international system, arms races, etc.),
-business (energy, music, sports, etc.)
-interpersonal relations (divorce cases, neighborhood disputes, etc.).
SkriptA slide deck will be made available.
LiteraturRelevant references will be indicated in the slide deck.
363-1065-00LDesign Thinking: Human-Centred Solutions to Real World Challenges Belegung eingeschränkt - Details anzeigen
Findet dieses Semester nicht statt.
W5 KP5GS. Brusoni
KurzbeschreibungThe goal of this course is to engage students in a multidisciplinary collaboration to tackle real world problems. Following a design thinking approach, students will work in teams to solve a set of design challenges that are organized as a one-week, a three-week, and a final six-week project in collaboration with an external project partner.

Information and application: Link
LernzielDuring the course, students will learn about different design thinking methods and tools. This will enable them to:
- Generate deep insights through the systematic observation and interaction of key stakeholders (empathy).
- Engage in collaborative ideation with a multidisciplinary team.
- Rapidly prototype and iteratively test ideas and concepts by using various materials and techniques.
InhaltThe purpose of this course is to equip the students with methods and tools to tackle a broad range of problems. Following a Design Thinking approach, the students will learn how to observe and interact with key stakeholders in order to develop an in-depth understanding of what is truly important and emotionally meaningful to the people at the center of a problem. Based on these insights, the students ideate on possible solutions and immediately validated them through quick iterations of prototyping and testing using different tools and materials. The students will work in multidisciplinary teams on a set of challenges that are organized as a one-week, a three-week, and a final six-week project with an external project partner. In this course, the students will learn about the different Design Thinking methods and tools that are needed to generate deep insights, to engage in collaborative ideation, rapid prototyping and iterative testing.

Design Thinking is a deeply human process that taps into the creative abilities we all have, but that get often overlooked by more conventional problem solving practices. It relies on our ability to be intuitive, to recognize patterns, to construct ideas that are emotionally meaningful as well as functional, and to express ourselves through means beyond words or symbols. Design Thinking provides an integrated way by incorporating tools, processes and techniques from design, engineering, the humanities and social sciences to identify, define and address diverse challenges. This integration leads to a highly productive collaboration between different disciplines.

For more information and the application visit: Link
Voraussetzungen / BesonderesOpen mind, ability to manage uncertainty and to work with students from various background. Class attendance and active participation is crucial as much of the learning occurs through the work in teams during class. Therefore, attendance is obligatory for every session. Please also note that the group work outside class is an essential element of this course, so that students must expect an above-average workload.

Please note that the class is designed for full-time MSc students. Interested MAS students need to send an email to Linda Armbruster to learn about the requirements of the class.
363-1082-00LEnabling Entrepreneurship: From Science to Startup Belegung eingeschränkt - Details anzeigen
Students should provide a brief overview (unto 1 page) of their business ideas that they would like to commercialise through the course. If they do not have an idea, they are required to provide a motivation letter stating why they would like to do this elective. If you are unsure about the readiness of your idea or technology to be converted into a startup, please drop me a line to schedule a call or meeting to discuss.

The total number of students will be limited to 40. It is preferable that the students already form teams of at least two persons, where both the team-members would like to do the course. The names of the team-members should be provided together with the business idea or the motivation letter submitted by the students.

The students should submit the necessary information and apply to Link until 23 August 2020.
W3 KP2VA. Sethi
KurzbeschreibungThis elective is relevant for students who have developed a technology and are keen to evaluate the steps in starting a startup. This is also relevant for students who would like to start a startup but do not have a technology, but are clear on a specific market and the impact they would like to create.
LernzielStudents have technology competence or an idea that they would like to convert into a startup. They are now in the process of evaluating the steps necessary to do so. In summary:

1. Students want to become entrepreneurs
2. The students can be from business or science & technology
3. The course will enable the students to identify the relevance of their technology or idea from the market relevance perspective and thereby create a business case to take it to market.
4. The students will have exposure to investors and entrepreneurs (with a focus on ETH spin-offs) through the course, to gain insight to commercialise their idea
InhaltThe students would cover the following topics, as the build their idea into a business case:

1. Technology excellence: this assumes that the student has achieved a certain degree of competence in the area of technology that he or she expects to bring to the market
2. Market need and market relevance: The student would then be expected to identify the possible markets that may find the technology of relevance. Market relevance implies the process of identification of how relevant the market perceives the technology, and whether this can sustain over a longer period of time
3. IP and IP strategy: Intellectual property, whether in the form of a patent or a trade secret, implies the secret ingredient that enables the student to achieve certain results that competitors are unable to copy. This enables the student (and subsequently the startup) to hold on to the market that they create with customers
4. Team including future capabilities required: a startup requires multiple people with complementary capabilities. They also need to be motivated while at the same time protecting the interests of the startup
5. Financials: There is a need of funding to achieve milestones. This includes funding for salaries and running of the company
6. Investors and funding options: There are multiple funding options for a startup. They all come with different advantages and limitations. It's important for a startup to recognise its needs and find the investors that fit these needs and are best aligned with the vision of the founders
7. Preparation of business case: The students will finally prepare the business case that can help them to articulate the link of the technology with the market need and its willingness to pay
8. Legal overview, company forms and shareholders’ agreements (including pitfalls)

The seminar includes talks from invited investors, entrepreneurs and legal experts regarding the importance of the various elements being covered in content, workshops and teamwork. There is a particular emphasis on market validation on each step of the journey, to ensure relevance.
SkriptSince the course will revolve around the ideas of the students, the notes will be for the sole purpose of providing guidance to the students to help convert their technologies or ideas into business cases for the purpose of forming startups. Theoretical subject matter will be kept to a minimum and is not the focus of the course.
LiteraturBook
Sethi, A. "From Science to Startup"
ISBN 978-3-319-30422-9
Voraussetzungen / BesonderesThis course is only relevant for those students who aspire to become entrepreneurs.

Students applying for this course are requested to submit a 1 page business idea or, in case they don't have a business idea, a brief motivation letter stating why they would like to do this course.

If you are unsure about the readiness of your idea or technology to be converted into a startup, please drop me a line to schedule a call or meeting to discuss.
851-0703-00LGrundzüge des Rechts
Studierende, die die Vorlesung "Grundzüge des Rechts für Bauwissenschaften" (851-0703-03L) oder "Grundzüge des Rechts" (851-0708-00L) belegt haben oder belegen werden, sollen sich in dieser Lerneinheit nicht einschreiben.

Besonders geeignet für Studierende D-ARCH, D-MAVT, D- MATL
W2 KP2VO.  Streiff Gnöpff
KurzbeschreibungDie Vorlesung führt in die Grundzüge der Rechtsordnung ein. Es werden Grundfragen des Verfassungs- und Verwaltungsrechts, des Privatrechts sowie des Europarechts behandelt.
LernzielStudierende erkennen grundlegende Strukturen der Rechtsordnung, verstehen ausgewählte Probleme des öffentlichen Rechts und des Privatrechts und können die erworbenen Grundlagen in weitergehenden rechtswissenschaftlichen Lehrveranstaltungen anwenden.
InhaltGrundlegende Konzepte des Rechts, Rechtsquellen.
Privatrecht: Vertragsrecht (inkl. Werk- und Ingenieurverträge), Deliktsrecht und Sachenrecht.
Öffentliches Recht: Grundrechte, Verwaltungsrecht (inkl. Bezüge zu Umwelt und Raum), Staat als Nachfrager (öffentliche Beschaffung), prozessuales Denken.
Grundzüge des Europarechts und des Strafrechts.
SkriptJaap Hage, Bram Akkermans (Hg.), Introduction to Law, Cham 2017 (Online-Ressource ETH Bibliothek)
LiteraturWeiterführende Unterlagen werden auf der Moodle-Lernumgebung bereitgestellt (vgl. Link).
851-0735-10LWirtschaftsrecht Belegung eingeschränkt - Details anzeigen
Maximale Teilnehmerzahl: 100

Besonders geeignet für Studierende D-ITET, D-MAVT
W2 KP2VP. Peyrot
KurzbeschreibungDie Vorlesung führt die Studierenden in praxisnaher Weise in die rechtlichen Aspekte der Gründung und Führung eines Unternehmens ein.
LernzielDie Studierenden verfügen über grundlegende Kenntnisse des Wirtschaftsrechts. Sie sind in der Lage, selbständig wirtschaftsrechtliche Problemstellungen zu erkennen und interessengerecht zu lösen.
Sie verfügen über folgende Kompetenzen:
- Sie verfügen über das Grundlagenwissen zur Gründung und Führung eines Unternehmens.
- Sie sind vertraut mit den Themen contracting, negotiation, claims management und dispute resolution
- Sie kennen die Bedeutung eines Systems zur Einhaltung der rechtlichen Rahmenordnung einzurichten (compliance).
- Sie können zum legal management des Unternehmens beitragen und rechtliche Fragestellungen mit Juristen besprechen.
- Sie verstehen das Recht als Teil der Unternehmensstrategie und als wertvolle Ressource für die Unternehmung.
SkriptEin umfassendes Skript wird auf der Plattform Moodle online zur Verfügung gestellt.
851-0738-00LGeistiges Eigentum: Eine Einführung
Besonders geeignet für Studierende D-CHAB, D-INFK, D-ITET, D-MAVT, D- MATL, D-MTEC
W2 KP2VM. Schweizer
KurzbeschreibungDie Vorlesung bietet eine Einführung in das schweizerische und europäische Immaterialgüterrecht (Marken-, Urheber-, Patent- und Designrecht). Auch werden die Aspekte des Wettbewerbsrechts behandelt, die für den Schutz geistiger Schöpfungen und unternehmens- oder produktbezogener Zeichen relevant sind. Die rechtlichen Grundlagen werden anhand aktueller Fälle erarbeitet.
LernzielZiel der Vorlesung ist es, ETH-Studierende in die Lage zu versetzen, zu erkennen, welche Schutzrechte die von ihnen geschaffenen Leistungen möglicherweise schützen oder verletzen können. Dadurch lernen die Studierenden, die immaterialgüterrechtlichen Chancen und Risiken bei der Entwicklung und Vermarktung von Produkten abzuschätzen. Dazu müssen sie die Schutzvoraussetzungen und den Schutzumfang der verschiedenen immaterialgüterrechtlichen Schutzrechte ebenso kennen wie die Probleme, die typischerweise bei der Durchsetzung von Schutzrechten auftreten. Diese Kenntnisse sollen praxisnah aufgrund von aktuellen Urteilen und Fällen vermittelt werden.

Ein weiteres Ziel ist es, den Studierenden zu ermöglichen, informiert an der aktuellen Diskussion über die Ziele und Wünschbarkeit des Schutzes geistiger Leistungen teilzunehmen, wie sie insbesondere auf den Gebieten des Urheberrechts (Stichworte fair use, Creative Commons, Copyleft) und Patentrechts (Software-Patente, patent trolls, patent thickets), geführt wird.
851-0738-01LDie Rolle des Geistigen Eigentums im Ingenieurwesen und den technischen Wissenschaften Belegung eingeschränkt - Details anzeigen
Maximale Teilnehmerzahl: 40

Besonders geeignet für Studierende D-BAUG, D-BIOL, D-BSSE, D-CHAB, D-ITET, D-MAVT
W2 KP2VK. Houshang Pour Islam
KurzbeschreibungPatente und andere Formen des Geistigen Eigentums haben in den letzten Jahrzehnten einen starken Bedeutungszuwachs im Alltag von Ingenieuren und Wissenschaftern erfahren. Ziel der Vorlesung ist es, einen Überblick über grundlegende Aspekte des Geistigen Eigentums zu vermitteln und die Vorlesungsteilnehmer in die Lage zu versetzen, das Wissen später im Berufsalltag einzusetzen.
LernzielDas Wissen über Geistiges Eigentum ist für Ingenieure und Wissenschafter in den letzten Jahrzehnten zunehmend wichtiger geworden und bildet mittlerweile eine Schlüsselqualifikation. Sowohl in Produktion und Vertrieb als auch in Forschung und Entwicklung sind sie dabei insbesondere mit Fragen zum Schutz von technischen Erfindungen und mit der Nutzung von Patentinformationen konfrontiert.

Im Rahmen der Vorlesung werden die Vorlesungsteilnehmer mit den praxisrelevanten Aspekten des Geistigen Eigentums vertraut gemacht und in die Lage versetzt, das erworbene Wissen später im Berufsalltag einzusetzen.

Unter anderem werden in der Vorlesung die folgenden Themen behandelt:
- Die Bedeutung von Innovationen in industrialisierten Ländern
- Überblick über die Formen des Geistigen Eigentums
- Der Schutz von technischen Erfindungen und die Absicherung der kommerziellen Umsetzung
- Patente als Quelle für technische und andere wichtige Informationen
- Praktische Aspekte des Geistigen Eigentum im Forschungsalltag, bei der Arbeit im Unternehmen und bei der Gründung von Startups.

Das in der Vorlesung vermittelte Wissen wird anhand von Beispielen aus verschiedenen technischen Bereichen veranschaulicht und vertieft.

Die Vorlesung umfasst praktische Übungen zur Nutzung und Recherche von Patentinformationen. Es wird dabei das Grundwissen vermittelt, wie Patentdokumente gelesen und ausgewertet werden und öffentlich zugängliche Patentdatenbanken genutzt werden können, um die benötigten Patentinformationen zu beschaffen und im Alltag einzusetzen.
Voraussetzungen / BesonderesDie Vorlesung ist für Studierende ingenieurwissenschaftlicher, naturwissenschaftlicher und anderer technischer Studienfächer geeignet.
Industriepraktikum
NummerTitelTypECTSUmfangDozierende
227-1550-10LInternship in Industry Belegung eingeschränkt - Details anzeigen
Nur für Elektrotechnik und Informationstechnologie MSc (Studienreglement 2018).
W12 KPexterne Veranstalter
KurzbeschreibungEs ist das Ziel der 12-wöchigen Praxis, Master-Studierenden die industriellen Arbeitsumgebungen näher zu bringen. Während dieser Zeit bietet sich ihnen die Gelegenheit, in aktuelle Projekte der Gastinstitution involviert zu werden.
Lernzielsiehe oben
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