Search result: Catalogue data in Spring Semester 2021
|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||2V||D. Helbing, N. Antulov-Fantulin, V. Vasiliauskaite|
|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.
|Content||Will be provided on a separate course webpage.|
|Lecture notes||Slides will be provided.|
|Literature||Grus, Joel. "Data Science from Scratch: First Principles with Python". O'Reilly Media, 2019.|
"A high-bias, low-variance introduction to machine learning for physicists"
Applications to Techno-Socio-Economic Systems:
"The hidden geometry of complex, network-driven contagion phenomena" (relevant for modeling pandemic spread)
"A network framework of cultural history"
"Science of science"
"Generalized network dismantling"
Further literature will be recommended in the lectures.
|Prerequisites / Notice||Good programming skills and a good understanding of probability & statistics and calculus are expected.|
|851-0165-00L||Questions Concerning the Philosophy of Mathematics, Theoretical Physics and Computer Science||W||3 credits||2S||G. Sommaruga, S. Wolf|
|Abstract||This seminar tackles questions of the philosophy of mathematics, of theoretical physics ad computer science which are rather non-standard such as: Are proofs really constitutive of mathematics? Why are applications of mathematics (to nature but also to mathematics itself) so fascinating and so hard to understand? etc.|
|Objective||The objective is not so much to get acquainted with basic concepts and theories in the philosophy of mathematics, of theoretical physics and computer science, but to reflect in a methodical way about what lies at the origin of these philosophies. Students should learn to articulate questions arising during their studies and to pursue them in a more systematic way.|
|Content||This seminar tackles questions of the philosophy of mathematics, of theoretical physics ad computer science which are rather non-standard such as: Are proofs really constitutive of mathematics? Why are applications of mathematics (to nature but also to mathematics itself) so fascinating and so hard to understand? Why do certain physical theories, e.g. quantum mechanics, need an "interpretation" whereas others don't? Is computer science part of discrete mathematics or a natural science? etc.|
|851-0097-00L||What Is Knowledge and Under What Conditions Are We Entitled to Claim Knowledge?||W||3 credits||2G||L. Wingert|
|Abstract||The seminar aims at a clarification of the concept of knowledge, as it is built in our experiential relations to the world. An analysis is needed of the difference between knowledge and belief, of the relation between objectivity and knowledge, and of the role of reasons for having knowledge. Additionally, the legitimacy of different types of knowledge claims should be evaluated.|
|Objective||On will able to evaluate the arguments pro and con the thesis, that knowledge is justified, true belief. Furthermore, one will gain some insights in the role of reasons for knowledge and in the merits and misgivings of a naturalistic account of knowledge. Finally, one will be a bit more familiar with some theories of philosophical epistemology (e.g. empiricism, rationalism).|
|851-0197-00L||Medieval and Early Modern Science and Philosophy||W||3 credits||2V||E. Sammarchi|
|Abstract||The course analyses the evolution of the relation between science and philosophy during the Middle Age and the Early Modern Period.|
|Objective||The 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 scientific texts written in the past ages.
|Content||The 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.|
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