Suchergebnis: Katalogdaten im Herbstsemester 2021

GESS Wissenschaft im Kontext (Science in Perspective) Information
Nur die in diesem Abschnitt aufgelisteten Fächer können als "GESS Wissenschaft im Kontext" angerechnet werden.
Weiter unten finden Sie die Kurse im Bereich "Typ B. Reflexion über fachspezifische Methoden und Inhalte" sowie den Bereich "Sprachkurse"

Im Bachelorstudium sind 6 KP und im Masterstudium 2 KP zu erwerben.

Studierende, die eine Lerneinheit bereits im Rahmen ihres Fachstudiums abgelegt haben, dürfen dieselbe Veranstaltung NICHT nochmals belegen!
Typ B: Reflexion über fachspezifische Methoden und Inhalte
Fachspezifische Lerneinheiten. Empfohlen für Studierende ab der Basisprüfung im Bachelor- oder für Studierende im Master- oder Promotionsstudium.

Studierende, die eine Lerneinheit bereits im Rahmen ihres Fachstudiums abgelegt haben, dürfen dieselbe Veranstaltung NICHT nochmals belegen!

Diese Lerneinheiten sind alle auch unter "Typ A" aufgelistet, d.h. sie sind grundsätzlich für alle Studierenden belegbar.
851-0101-86LComplex Social Systems: Modeling Agents, Learning, and Games Belegung eingeschränkt - Details anzeigen
Number of participants limited to 100.

Prerequisites: Basic programming skills, elementary probability and statistics.
W3 KP2SN. Antulov-Fantulin, T. Asikis, D. Helbing
KurzbeschreibungThis course introduces mathematical and computational models to study techno-socio-economic systems and the process of scientific research. Students develop a significant project to tackle techno-socio-economic challenges in application domains of complex systems. They are expected to implement a model and communicating their results through a seminar thesis and a short oral presentation.
LernzielThe students are expected to know a programming language and environment (Python, Java or Matlab) as a tool to solve various scientific problems. The use of a high-level programming environment makes it possible to quickly find numerical solutions to a wide range of scientific problems. Students will learn to take advantage of a rich set of tools to present their results numerically and graphically.

The students should be able to implement simulation models and document their skills through a seminar thesis and finally give a short oral presentation.
InhaltStudents are expected to implement themselves models of various social processes and systems, including agent-based models, complex networks models, decision making, group dynamics, human crowds, or game-theoretical models.

Part of this course will consist of supervised programming exercises. Credit points are finally earned for the implementation of a mathematical or empirical model from the complexity science literature and the documentation in a seminar thesis.
SkriptThe lecture slides will be presented on the course web page after each lecture.
LiteraturAgent-Based Modeling

Social Self-Organization

Traffic and related self-driven many-particle systems
Reviews of Modern Physics 73, 1067

An Analytical Theory of Traffic Flow (collection of papers)

Pedestrian, Crowd, and Evacuation Dynamics

The hidden geometry of complex, network-driven contagion phenomena (relevant for modeling pandemic spread)

Further literature will be recommended in the lectures.
Voraussetzungen / BesonderesThe number of participants is limited to the size of the available computer teaching room. The source code related to the seminar thesis should be well enough documented.

Good programming skills and a good understanding of probability & statistics and calculus are expected.
Fachspezifische KompetenzenKonzepte und Theoriengeprüft
Verfahren und Technologiengeprüft
Methodenspezifische KompetenzenAnalytische Kompetenzengeprüft
Medien und digitale Technologiengefördert
Soziale KompetenzenKommunikationgeprüft
Kooperation und Teamarbeitgeprüft
Menschenführung und Verantwortunggeprüft
Selbstdarstellung und soziale Einflussnahmegeprüft
Sensibilität für Vielfalt geprüft
Persönliche KompetenzenAnpassung und Flexibilitätgeprüft
Kreatives Denkengeprüft
Kritisches Denkengeprüft
Integrität und Arbeitsethikgeprüft
Selbstbewusstsein und Selbstreflexion geprüft
Selbststeuerung und Selbstmanagement geprüft
851-0650-00LAI4Good Belegung eingeschränkt - Details anzeigen W3 KP2GJ. D. Wegner
KurzbeschreibungThe AI4Good course is a hackathon turned into a full course. At the beginning, stakeholders active in the development sector will describe several problems that could be solved with a machine learning approach. Students will spend the semester on designing, implementing, and testing suitable solutions using machine learning. Progress will be discussed with all course members.
LernzielGiven a specific problem in global development, students shall learn to self-responsibly design, implement and experimentally evaluate a suitable solution. Students will also learn to critically evaluate their ideas and solutions together with all course members in a broader context that go beyond mere technical solutions, but touch on ethics, local culture etc., too.
InhaltThe AI4Good course is a hackathon turned into a full course. At the beginning of the course, stakeholders (e.g., NGOs) active in the development sector will describe several problems that could be solved with a machine learning approach. Organizers of the course will make sure that only those problems are selected that are suitable for a machine learning approach and where sufficient amounts of data (and labels) are available. Students will organize themselves into small groups of 3-5 students, where each group works on solving a specific problem. Students will spend the semester on designing, implementing, and testing suitable solutions using machine learning. Every two weeks, each group will present ideas and progress during a short presentation followed by a discussion with all course members. At the end of the course, students will present their final results and submit source code. In addition, they will describe the developed method in form of a scientific paper of 8 pages. Grading will depend on the source code, the paper, and active participation in class.

Note: The course AI4Good is not related to Hack4Good, which is a students' initiative organized by the Analytics Club at ETH. For more information about Hack4Good check out the website: Link.
Voraussetzungen / BesonderesStudents with a strong background in machine learning and excellent programming skills (preferably in Python)
851-0175-00LImages of the HumanW3 KP2GJ. L. Gastaldi
KurzbeschreibungThis seminar will explore the multiple transformations of the conception of the “human” in the face of the current scientific, social and technological challenges, focusing on those related to recent digital technologies and practices. The lectures will be delivered by researchers from ETH and abroad, with different disciplinary backgrounds in the humanities and the social sciences.
LernzielBy the end of the course, students will be able to describe and compare different conceptions of the human at work in multiple fields of the humanities and the social sciences. They will be able to evaluate both the differences and the convergences between those conceptions, and critically assess their relation to current trends in science, technology and society, particularly in the context of new digital practices.
InhaltThe remarkable development of AI in the past decade has brought about a renewed urge to rethink our image of the "human". In this way, computer science and technology join other scientific disciplines having experienced the same need in the face of current challenges, such as climate change or the global pandemic, which question the place of the human in its environment. Such circumstances reveal that a science of the human is today more necessary than ever. For this reason, the Turing Centre's lecture series of this year will be dedicated to exploring the multiple images of the human at work across the human sciences and their transformation as a consequence of the current global challenges. In line with the Turing Centre's activities, the focus will be on challenges related to recent digital technologies and practices. Various researchers from ETH and abroad, with different disciplinary backgrounds in the humanities and the social sciences, will present what they consider crucial concepts, methods, challenges, and limits in our investigations about the human and its relation to machines, animals and nature.
851-0125-65LA Sampler of Histories and Philosophies of Mathematics Belegung eingeschränkt - Details anzeigen
Besonders geeignet für Studierende D-CHAB, D-INFK, D-ITET, D-MATH, D-PHYS
W3 KP2VR. Wagner
KurzbeschreibungThis 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.
LernzielThe 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
851-0197-00LMedieval and Early Modern Science and PhilosophyW3 KP2VE. Sammarchi
KurzbeschreibungThe course analyses the evolution of the relation between science and philosophy during the Middle Age and the Early Modern Period.
LernzielThe course aims are:
- to introduce students to the philosophical dimension of science;
- to develop a critical understanding of scientific notions;
- to acquire skills in order to read and comment on scientific texts written in the past ages.
InhaltThe course is focused on the investigation of scientific thought between 1000 and 1700, that is to say the period that saw the flourishing of natural philosophy and the birth of the modern scientific method. Several case-studies, taken from different scientific fields (especially algebra, astronomy, and physics) are presented in class in order to examine the relation between science and philosophy and the shift from medieval times to the early modern world.
851-0742-01LContract Design II Belegung eingeschränkt - Details anzeigen
This course is taught by Professor Alexander Stremitzer (Link). To be considered for Contract Design II, you must have completed Contract Design I in the same semester. Students can only register for Contract Design II after having obtained approval by Prof. Stremitzer.
W1 KP1UA. Stremitzer
KurzbeschreibungContract Design II is a masterclass in the form of an interactive clinic that allows you to deepen your understanding of contracting by applying insights from Contract Design I to a comprehensive case study. Together with your classmates, you are going to advise a (hypothetical) client organization planning to enter a complex transaction on how to structure the underlying contract.
LernzielThere is a possibility that representatives from companies that were previously engaged in similar deals will visit us in class and tell you about their experience firsthand. In Contract Design I, you will receive more detailed information on the content and learning objectives of Contract Design II. If you have urgent questions, please do not hesitate to send an e-mail to Professor Stremitzer’s Teaching Assistant Diego Caldera (Link).
Voraussetzungen / BesonderesTo enable you to work under the close supervision of your professor and his team, only a small group of students with backgrounds in law, business, or engineering is admitted to this course. This simulation is time-consuming and challenging. Hence, we can only admit the most successful and motivated students to this class. Further information on the application process will follow.
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