Search result: Catalogue data in Spring Semester 2020
|GESS Science in Perspective |
Only the courses listed below will be recognized as "GESS Science in Perspective" courses.
Further below you will find courses under the category "Type B courses Reflections about subject specific methods and content" as well as the language courses.
During the Bachelor’s degree Students should acquire at least 6 ECTS and during the Master’s degree 2 ECTS.
Students who already took a course within their main study program are NOT allowed to take the course again.
| Type B: Reflection About Subject-Specific Methods and Contents|
Subject-specific courses: Recommended for bachelor students after their first-year examination and for all master- or doctoral students.
Students who already took a course within their main study program are NOT allowed to take the same course again.
All these courses are listed under the category “Typ A”, this means, every student can enroll in these courses.
|851-0585-38L||Data Science in Techno-Socio-Economic Systems |
Number of participants limited to 80
This course is thought be for students in the 5th semester or above with quantitative skills and interests in modeling and computer simulations.
Particularly suitable for students of D-INFK, D-ITET, D-MAVT, D-MTEC, D-PHYS
|W||3 credits||3S||N. Antulov-Fantulin|
|Abstract||This course introduces how techno-socio-economic systems in our complex society can be better understood with techniques and tools of data science. Students shall learn how the fundamentals of data science are used to give insights into the research of complexity science, computational social science, economics, finance, and others.|
|Objective||The goal of this course is to qualify students with knowledge on data science to better understand techno-socio-economic systems in our complex societies. This course aims to make students capable of applying the most appropriate and effective techniques of data science under different application scenarios. The course aims to engage students in exciting state-of-the-art scientific tools, methods and techniques of data science. |
In particular, lectures will be divided into research talks and tutorials. The course shall increase the awareness level of students of the importance of interdisciplinary research. Finally, students have the opportunity to develop their own data science skills based on a data challenge task, they have to solve, deliver and present at the end of the course.
|Prerequisites / Notice||Good programming skills and a good understanding of probability & statistics and calculus are expected.|
|851-0740-00L||Big Data, Law, and Policy |
Number of participants limited to 35
Students will be informed by 1.3.2020 at the latest.
|W||3 credits||2S||S. Bechtold|
|Abstract||This course introduces students to societal perspectives on the big data revolution. Discussing important contributions from machine learning and data science, the course explores their legal, economic, ethical, and political implications in the past, present, and future.|
|Objective||This course is intended both for students of machine learning and data science who want to reflect on the societal implications of their field, and for students from other disciplines who want to explore the societal impact of data sciences. The course will first discuss some of the methodological foundations of machine learning, followed by a discussion of research papers and real-world applications where big data and societal values may clash. Potential topics include the implications of big data for privacy, liability, insurance, health systems, voting, and democratic institutions, as well as the use of predictive algorithms for price discrimination and the criminal justice system. Guest speakers, weekly readings and reaction papers ensure a lively debate among participants from various backgrounds.|
|851-0732-03L||Intellectual Property: An Introduction |
Number of participants limited to 180
Particularly suitable for students of D-ARCH, D-BIOL, D-CHAB, D-INFK, D-ITET, D-MAVT, D- MATL, D-MTEC.
|W||2 credits||2V||S. Bechtold, M. Schonger|
|Abstract||The course introduces students to the basics of the intellectual property system and of innovation policy. Areas covered include patent, copyright, trademark, design, know-how protection, open source, and technology transfer. The course looks at Swiss, European, U.S. and international law and uses examples from a broad range of technologies. Insights can be used in academia, industry or start-ups.|
|Objective||Intellectual property issues become more and more important in our society. In order to prepare students for their future challenges in research, industry or start-ups, this course introduces them to the foundations of the intellectual property system. The course covers patent, copyright, trademark, design, know-how protection, open source, and technology transfer law. It explains links to contract, antitrust, Internet, privacy and communications law where appropriate. While the introduction to these areas of the law is designed at a general level, examples and case studies come from various jurisdictions, including Switzerland, the European Union, the United States, and international law.|
In addition, the course introduces students to the fundamentals of innovation policy. After exposing students to the economics of intellectual property protection, the course asks questions such as: Why do states grant property rights in inventions? Has the protection of intellectual property gone too far? How do advances in biotechnology and the Internet affect the intellectual property system? What is the relationship between open source, open access and intellectual property? What alternatives to intellectual property protection exist?
Knowing how the intellectual property system works and what kind of protection is available is useful for all students who are interested in working in academia, industry or in starting their own company. Exposing students to the advantages and disadvantages of the intellectual property system enables them to participate in the current policy discussions on intellectual property, innovation and technology law. The course will include practical examples and case studies as well as guest speakers from industry and private practice.
Particularly suitable for students of D-INFK, D-ITET
|W||2 credits||2V||C. von Zedtwitz|
|Abstract||Introduction to the basics of Telecommunications Law for non-lawyers. |
The course deals with the legal regulations and principles that apply to telecom network operators and telecom service providers (fixed-line and mobile phone).
|Objective||By analyzing the most relevant legal provisions for a telecom provider in Switzerland students will learn about the main concepts of Swiss law. No previous legal courses required.|
|Content||1. History of Swiss Telecommunications Law|
2. Regulation of network access (essential facility doctrine, types of access)
3. Universal Service
4. Phone service contracts (fixed line and mobile phone service)
5. Mobil communication radiation regulation
6. Telecommunication secrecy
|Lecture notes||The powerpoint slides presented in the course will be made availabe online. In addition, links to relevant legal decisions and regulations will be accessible on the course website.|
|Literature||No mandatory readings.|
|Prerequisites / Notice||Short written exam at the end of the semester (scope and materials to be defined during the course).|
|851-0734-00L||Information Security Law|
Does not take place this semester.
Particularly suitable for students of D-INFK, D-ITET
|Abstract||Introduction to Information Security Law for non-legal students respectively prospective decision-makers in companies and public authorities who will have to deal with information security issues (CIOs, COOs, CEOs). The lectures will focus on the legal aspects of the security of ICT infrastructures, including networks (Internet), and of the transported and processed information.|
|Objective||The objective is to understand the meaning and aims of information security and the legal framework, to become acquainted with legal instruments available to provide effective protection for infrastructures and sensitive legal assets and to present an analysis of possible legal loopholes and potential measures. No prior legal knowledge is required for those wishing to attend these lectures.|
|Content||The lectures will deal with industry-specific as well as cross-sector specific themes involving both technology and law from the areas of data protection law, computer crimes, statutory duties of confidentiality, telecommunication surveillance (Internet), electronic signatures, liability etc.|
|Lecture notes||The lectures will be accompanied by powerpoint slide presentations, downloadable before the lectures begin, or available as hard copy at the lectures themselves.|
|Literature||References to further literature sources will be given in the lectures.|
|851-0588-00L||Introduction to Game Theory |
Number of participants limited to 480.
Particularly suitable for students of D-INFK, D-MATH
|W||3 credits||1V||H. Nax, B. Pradelski|
|Abstract||This course introduces the foundations of game theory with a focus on its basic mathematical principles. It treats models of social interaction, conflict and cooperation, the origin of cooperation, and concepts of strategic decision making behavior. Examples, applications, theory, and the contrast between theory and empirical results are particularly emphasized.|
|Objective||Learn the fundamentals, models, and logic of thinking about game theory. Learn basic mathematical principles. Apply formal game theory models to strategic interaction situations and critically assess game theory's capabilities through a wide array of applications and experimental results.|
|Content||Game theory provides a unified mathematical language to study interactions amongst different types of individuals (e.g. humans, firms, nations, animals, etc.). It is often used to analyze situations involving conflict and/or cooperation. The course introduces the basic concepts of both non-cooperative and cooperative game theory (players, strategies, coalitions, rules of games, utilities, etc.) and explains the most prominent game-theoretic solution concepts (Nash equilibrium, sub-game perfection, Core, Shapley Value, etc.). We will also discuss standard extensions (repeated games, incomplete information, evolutionary game theory, signal games, etc.). |
In each part of the course, we focus on examples and on selected applications of the theory in different areas. These include analyses of cooperation, social interaction, of institutions and norms, social dilemmas and reciprocity as well as applications on strategic behavior in politics and between countries and companies, the impact of reciprocity, in the labor market, and some applications from biology. Game theory is also applied to control-theoretic problems of transport planning and computer science.
As we present theory and applications, we will also discuss how experimental and other empirical studies have shown that human behavior in the real world often does not meet the strict requirements of rationality from "standard theory", leading us to models of "behavioural" and "experimental" game theory.
By the end of the course, students should be able to apply game-theoretic in diverse areas of analysis including > controlling turbines in a wind park, > nations negotiating international agreements, > firms competing in markets, > humans sharing a common resource, etc.
|Lecture notes||See literature below. In addition we will provide additional literature readings and publish the lecture slides directly after each lecture.|
|Literature||K Binmore, Fun and games, a text on game theory, 1994, Great Source Education|
SR Chakravarty, M Mitra and P Sarkar, A Course on Cooperative Game Theory, 2015, Cambridge University Press
A Diekmann, Spieltheorie: Einführung, Beispiele, Experimente, 2009, Rowolth
MJ Osborne, An Introduction to Game Theory, 2004, Oxford University Press New York
J Nash, Non-Cooperative Games, 1951, Annals of Mathematics
JW Weibull, Evolutionary game theory, 1997, MIT Press
HP Young, Strategic Learning and Its Limits, 2004, Oxford University Press
|851-0591-01L||BETH - Blockchain for Sustainability |
Does not take place this semester.
Number of participants limited to 200
Particularly suitable for students of D-INFK, D-MTEC, D-ITET, D-MAVT,D-PHYS
|W||3 credits||4G||D. Helbing|
|Abstract||Blockchain and Internet of Things technologies hold the promise to transform our societies and economies. While IoT devices allow us to measure all kinds of activity by humans and machines, the blockchain allows us to securely time-stamp and value this data and even give it a price to trade it on (new) markets. We explore this potential with a specific focus on sustainable development.|
|Objective||The course provides opportunities to gain fundamental understanding of promising new technologies as well as develop creative decentralized solutions for societal challenges using these technologies.|
Participants will learn the fundamentals of blockchain technology, its mechanisms, design parameters and potential for decentralized solutions. Those with software development skills will then further explore the blockchain to develop hands-on decentralized applications and smart contracts. Non-coding participants will further explore how these technologies could be used to design new economic systems. These new cryptoeconomic systems should give citizens multiple incentives to increase cooperation, health, recycling, or education and other positive externalities and to decrease emissions, waste, noise, or stress and other negative externalities. During the hackathon, participants will work in mixed teams on concrete challenges addressing some of the pressing global challenges our societies face, like climate change, financial instability, energy, or mass migration, etc. The aim is to develop decentralized approaches towards a sustainable, sharing circular economy using blockchain and IoT technologies.
Teams will produce a short report (about 10 pages), demonstrate their hackathon prototype based on blockchain technology (Ethereum platform) and present to a interdisciplinary jury on the last day. Throughout the course, participants will hone their critical thinking abilities by leaving their own discipline and discussing best approaches to solve global complex challenges in an international, multi-disciplinary setting with invited subject matter experts and peers from all around the world.
We encourage students with no programming experience, who are interested in the potential of blockchain and IoT to address global challenges, to apply as well!
|851-0739-01L||Sequencing Legal DNA: NLP for Law and Political Economy|
Particularly suitable for students of D-INFK, D-ITET, D-MTEC
|W||3 credits||2V||E. Ash|
|Abstract||This course explores the application of natural language processing techniques to texts in law, politics, and the news media. Students will put these tools to work in a course project.|
|Objective||Law is embedded in language. An essential task for a judge, therefore, is reading legal texts to interpret case facts and apply legal rules. Can an artificial intelligence learn to do these tasks? The recent and ongoing breakthroughs in natural language processing (NLP) hint at this possibility. |
Meanwhile, a vast and growing corpus of legal documents are being digitized and put online for use by the public. No single human could hope to read all of them, yet many of these documents remain untouched by NLP techniques. This course invites students to participate in these new explorations applying NLP to the law -- that is, sequencing legal DNA.
|Content||NLP technologies have the potential to assist judges in their decisions by making them more efficient and consistent. On the other hand, legal language choices -- as in legal choices more generally -- could be biased toward some groups, and automated systems could entrench those biases. We will explore, critique, and integrate the emerging set of tools for debiasing language models and think carefully about how notions of fairness should be applied in this domain. |
More generally, we will explore the use of NLP for social science research, not just in the law but also in politics, the economy, and culture. In a semester paper, students (individually or in groups) will conceive and implement their own research project applying natural language tools to legal or political texts.
|Prerequisites / Notice||Some programming experience in Python is required, and some experience with NLP is highly recommended.|
|851-0739-02L||Sequencing Legal DNA: NLP for Law and Political Economy (Course Project)|
This is the optional course project for "Building a Robot Judge: Data Science for the Law."
Please register only if attending the lecture course or with consent of the instructor.
Some programming experience in Python is required, and some experience with text mining is highly recommended.
|W||2 credits||2V||E. Ash|
|Abstract||This is the companion course for extra credit for a more substantial project, for the course "Sequencing Legal DNA: NLP for Law and Political Economy".|
|851-0125-65L||A Sampler of Histories and Philosophies of Mathematics|
Particularly suitable for students D-CHAB, D-INFK, D-ITET, D-MATH, D-PHYS
|W||3 credits||2V||R. Wagner|
|Abstract||This course will review several case studies from the ancient, medieval and modern history of mathematics. The case studies will be analyzed from various philosophical perspectives, while situating them in their historical and cultural contexts.|
|Objective||The course aims are:|
1. To introduce students to the historicity of mathematics
2. To make sense of mathematical practices that appear unreasonable from a contemporary point of view
3. To develop critical reflection concerning the nature of mathematical objects
4. To introduce various theoretical approaches to the philosophy and history of mathematics
5. To open the students' horizons to the plurality of mathematical cultures and practices
|851-0170-00L||The Birth of Formal Sciences: History and Philosophy of the Relation Between Logic and Mathematics||W||3 credits||2V||J. L. Gastaldi|
|Abstract||Formal knowledge, such as mathematics and logic, has a singular capacity to resist historical critique. But what if formality itself had a history - a recent birth and a foreseeable decline? In this course, we will explore this hypothesis by critically assessing the novel relationship between mathematics and logic that emerged in the 19th century, forging our notion of formal.|
|Objective||During the course, students will be able to:|
-Acquire a general perspective on the history of formal logic
-Review relevant aspects of the history of modern mathematics
-Obtain philosophical and historical tools for critically assessing the status of formal sciences
-Develop a critical understanding of the notion of formal
-Discuss the methodological capabilities of historical epistemology
|Content||Knowledge reputed to be formal, such as mathematics and logic, has a singular capacity to resist historical critique. Indeed, from a traditional perspective, a historical account of a purely formal statement, like a theorem, can hardly do more than show the inevitable path that led to its evident and thenceforth everlasting truth. But what if formality itself had a history - a relative recent birth and a foreseeable decline? In this course, we will explore this hypothesis by critically assessing the conditions, impact and limits of the novel relationship between mathematics and logic that emerged in the 19th century, forging both the modern notion of formal and the subsequent epistemological status of formal sciences. After discussing the difficulties of a historical (or archaeological, in the sense that M. Foucault gives to this term) approach to formal knowledge, we will present the principal historical circumstances providing the conditions for an unprecedented association between logic and mathematics. This will give us the means to undertake the detailed study of that association, within the context of the most prominent attempts to provide formal deductive languages in the 19th century: those of George Boole and Gottlob Frege. Finally, we will address the limitations manifested by those projects at the turn of the 20th century, putting them into perspective to assess the transformation our notion of formal is experiencing as a result of the proliferation of computational practices.|
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