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56906-01 - Seminar: Einführung in Machine Learning 3 CP

Semester spring semester 2020
Course frequency Once only
Lecturers Gerhard Lauer (gerhard.lauer@unibas.ch, Assessor)
Content Machine Learning (ML) is a subset of artificial intelligence and a powerful tool to understand data, even predicting data. The seminar is an introduction to basic concepts and application of ML for research issues in the humanities and social sciences.
Learning objectives The objective is to learn how to run machine learning for research in social sciences and humanities. Students will read and discuss basic papers in the field of ML in class, take part in hands-on sessions to practice ML, and write a research report in which they demonstrate their knowledge of ML.

 

Course application Belegen
Language of instruction English
Use of digital media No specific media used

 

Interval weekly
Date 25.02.2020 – 26.05.2020
Time Tuesday, 10.15-12.00 Kollegienhaus, Seminarraum 106
Date Time Room
Tuesday 25.02.2020 10.15-12.00 Kollegienhaus, Seminarraum 106
Tuesday 03.03.2020 10.15-12.00 Fasnachtsferien
Tuesday 10.03.2020 10.15-12.00 Kollegienhaus, Seminarraum 106
Tuesday 17.03.2020 10.15-12.00 Kollegienhaus, --
Tuesday 24.03.2020 10.15-12.00 Kollegienhaus, --
Tuesday 31.03.2020 10.15-12.00 Kollegienhaus, --
Tuesday 07.04.2020 10.15-12.00 Kollegienhaus, --
Tuesday 14.04.2020 10.15-12.00 Kollegienhaus, --
Tuesday 21.04.2020 10.15-12.00 Kollegienhaus, --
Tuesday 28.04.2020 10.15-12.00 Kollegienhaus, --
Tuesday 05.05.2020 10.15-12.00 Kollegienhaus, --
Tuesday 12.05.2020 10.15-12.00 Kollegienhaus, --
Tuesday 19.05.2020 10.15-12.00 Kollegienhaus, --
Tuesday 26.05.2020 10.15-12.00 Kollegienhaus, --
Modules Modul: Digital Humanities, Culture and Society (Master's degree subject Digital Humanities)
Assessment format continuous assessment
Assessment details Portfolio Students will write a research report in which they introduce a question of their choice, which they attempt to answer using machine learning.
This report will be assessed as either a pass or a fail.
Assessment registration/deregistration Reg.: course registration; dereg.: not required
Repeat examination no repeat examination
Scale Pass / Fail
Repeated registration no repetition
Responsible faculty Faculty of Humanities and Social Sciences, studadmin-philhist@unibas.ch
Offered by Digital Humanities Lab

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