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Root number
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458670 |
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Semester
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FS2026 |
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Type of course
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Lecture |
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Allocation to subject
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Economics |
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Type of exam
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not defined |
| Title |
PhD-Machine Learning in Economics |
| Description |
*** IMPORTANT ***
For the most updated administrative course information (date changes, room changes etc) please always refer to the KSL page only and not to the Info page in ILIAS – the ILIAS infopage will not be updated!
Prof. Dr. Costanza Stettler (former Naguib)
The aim of this course is to provide students with an overview of the most common machine learning methods that are currently acquiring more and more importance in the economic analysis. Both the theoretical framework and implementation technique of the methods will be presented. Theory lectures will be complemented by exercise sessions in the computer lab. The software used in this course is RStudio, which can be freely downloaded. In particular, this course starts from the basics of model selection and introduces Lasso and Ridge regression, as well as the random tree, boosting, bagging, the random forest and its recent extension to the causal forest.
Assessment:
As final examination, students are expected to write a short paper (10 pages) in which they will apply one or more of the methods studied during the course. This paper accounts for 100% of the final grade. PhD students have the option of further preparing a presentation, in which they will detail a recent paper on machine learning methods. The presentation is graded with PASS/FAIL and allows PhD students to receive 6 ECTS (instead of 4.5 ECTS) for this course.
Lecture:
Thursday, 14.15 - 16.00 h, A322, PC Pool , UniS
1st term submission paper:29th May 2026
2nd term submission paper: 28th August 2026
Presentations: Tba |
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ILIAS-Link (Learning resource for course)
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No registration/deregistration in CTS (Admission in ILIAS possible).
ILIAS
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Link to another web site
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| Lecturers |
Prof. Dr.
Costanza Stettler, Department of Economics ✉
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ECTS
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6 |
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Recognition as optional course possible
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No |
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Grading
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1 to 6 |
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| Dates |
Thursday 14:15-16:00 Weekly
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Friday 29/5/2026 00:00-23:55
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Friday 28/8/2026 00:00-23:55
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Rooms
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| External rooms |
A322, PC Pool, UniS
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| Students please consult the detailed view for complete information on dates, rooms and planned podcasts. |
User:
Öffentlicher Bereich
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