Philosophy & Economics

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Veranstaltungstitel Data Literacy: Machine Learning, Data Visualisation, and Philosophy of Statistics
Kennzeichen 50033
Veranstaltungsart Blockseminar
Fachgruppe Philosophie
Semester Sommer 2022
Dozent(en) Sebastian Zezulka
Simon Döbele
Konstantin Lehmann
Empfehlung(en) Studiensemester 4. Semester (P&E Bachelor)
6. Semester (P&E Bachelor)
BA höhere Fachsemester (> 6) (P&E Bachelor)
Bereich(e) P6.v: Theoretische Philosophie
P5*: Wissenschaftstheorie II


Scientific, policy, as well as corporate decisions should be based on good evidence and solid reasoning. Often, this requires decision makers to consider large amounts of data and to use quantitative methods to analyse them. This course equips students with solid foundations to apply, communicate and reflect on quantitive methods. It enables students to become data literate along three dimensions. First, an introduction to standard machine learning methods. Second, practical skills in structuring a data science project and communicating the results. Third, understanding the philosophical reflections on the applied methods. A special emphasis of the course is to give students a very first hands-on experience with Python. On Sunday, we will offer three parallel workshops on philosophy of statistics, practical data visualisation, and a data science project.

Participation in the online seminar “Introduction to Python” on Friday, 06.05.2022, 09.00-12.00h and the weekend seminar from 10.-12.06.2022 in Bayreuth is obligatory. A non-mandatory, online Q&A session will be offered on Wednesday, 25.05.2022, 17.00-18.30h to help with the data science practicals. To be successful in this course, students must come prepared to class. A student is adequately prepared if she has carefully completed all of the required readings or practical assignments and has compiled some comments or questions.


online via:

Erfordernisse zum Punkteerwerb

2 CP: come prepared (readings and data sicence practicals), active participation
5 CP: same as 2 CP + write a philosophical essay or report on a data science project you did afterwards

Zugehörige Termine
von - bis Ort  
Fri. 10.06.2022 - Sun. 12.06.2022 S 5, GW II
Fri. 06.05.2022 Vorbesprechung (online)
Sat. 11.06.2022 S 5, GW II
Sun. 12.06.2022 S 5, GW II