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Seminar on statistical foundations of data science
Lecturer:
UnivProf.Dr. Axel Munk
Course typ:
Seminar
Place:
(5.101 Seminarraum (Informatik/Stochastik))
Semester:
SoSe 2023
Times:
Fri.. 10:15 - 11:45 (weekly)
First appointment: Friday, 14.04.2023 10:15 - 11:45, Room: (5.101 Seminarraum (Informatik/Stochastik))
Course number:
504748
Performance accreditation:
→Ab hier automatisch erfasste Informationen / Beyond this point, the information is filled in automatically← Prüfungsleistung(en) je Modul / Exam details per module: * [(B.Mat.3441.Mp) Seminar im Zyklus "Angewandte und Mathematische Stochastik"][1] * Andere Prüfungsform: Mo, 15.05.2023 * [(B.Mat.3444.Mp) Seminar im Zyklus "Mathematische Statistik"][2] * Andere Prüfungsform: Mo, 15.05.2023 * [(B.Mat.3447.Mp) Seminar im Zyklus "Statistische Grundlagen der Data Science"][3] * Andere Prüfungsform: Mo, 15.05.2023 * [(M.Mat.4841.Mp) Seminar on applied and mathematical stochastics][4] * Andere Prüfungsform: Mo, 15.05.2023 * [(M.Mat.4844.Mp) Seminar on mathematical statistics][5] * Andere Prüfungsform: Mo, 15.05.2023 * [(M.Mat.4847.Mp) Seminar on statistical foundations of data science][6] * Andere Prüfungsform: Mo, 15.05.2023 [1]: https://ecampus.uni-goettingen.de/h1/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=33526&periodId=271 [2]: https://ecampus.uni-goettingen.de/h1/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=38676&periodId=271 [3]: https://ecampus.uni-goettingen.de/h1/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=33535&periodId=271 [4]: https://ecampus.uni-goettingen.de/h1/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=40031&periodId=271 [5]: https://ecampus.uni-goettingen.de/h1/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=40040&periodId=271 [6]: https://ecampus.uni-goettingen.de/h1/pages/startFlow.xhtml?_flowId=detailView-flow&unitId=40049&periodId=271
Further information from Stud.IP about this course
Home institute: Bereich Mathematik
Participants registered in Stud.IP: 24
Number of postings in Stud.IP forum: 2
Number of documents in the Stud.IP download area: 3