| Dozent/in |
Dr. rer. publ. Massimo Mannino |
| Veranstaltungsart |
Vorlesung |
| Code |
HS261041 |
| Semester |
Herbstsemester 2026 |
| Durchführender Fachbereich |
Wirtschaftswissenschaften |
| Studienstufe |
Master |
| Termin/e |
Fr, 18.09.2026, 08:15 - 14:00 Uhr, 3.B52
Fr, 25.09.2026, 08:15 - 14:00 Uhr, 2.A07
Fr, 30.10.2026, 08:15 - 14:00 Uhr, 4.B47
Fr, 11.12.2026, 08:15 - 14:00 Uhr, 2.A10 |
| Umfang |
Blockveranstaltung |
| Turnus |
Block course |
| Inhalt |
The lecture familiarizes students with a wide range of models in the field of Supervised Machine Learning. The course will focus on practical machine learning applications and teach data science techniques that enable students to solve real-world problems from the business world. By means of R, students will learn to estimate and visualize model results and communicate results efficiently. The integrated exercises discuss application examples from business administration and economics. |
| Lernziele |
1) Students can independently prepare and analyze data with R.
2) Students can apply methods in the field of Supervised Machine Learning.
3) Students are able to visualize model results with R.
4) Students can communicate model results effectively. |
| Voraussetzungen |
Solid knowledge in econometrics, statistics and R. |
| Sprache |
Englisch |
| Begrenzung |
24 Students
If the maximum number of participants is reached, students of the MA in Economics and Management will be given priority. In this case, please contact the wf@unilu.ch |
| Anmeldung |
Binding registration takes place via the UniPortal; see notes below in the «Proof of Performance» field.
For course information and materials, registration on the OLAT e-learning platform is required from 31 August – 13 September 2026. The students themselves are responsible for verifying the course’s creditability towards their degree program.
Direct link to the OLAT course: https://lms.uzh.ch/url/RepositoryEntry/17903616234 |
| Leistungsnachweis |
***IMPORTANT*** To receive course credit and earn academic credits, registration via the Uni Portal from 31 August (starting at 9:00 a.m.) – 13 September 2026 is MANDATORY.
Late registrations and withdrawals will not be accepted. Once the registration period has ended, participation in the course is MANDATORY. If the course is not completed without a valid reason and without proper withdrawal (including supporting documentation; see the Exam Guidelines), the course will be considered failed (grade 1). |
| Abschlussform / Credits |
Written paper / Individual or group presentation / 3 Credits
|
| Hörer-/innen |
Nach Vereinbarung |
| Kontakt |
massimo.mannino@novalytica.com |
| Anzahl Anmeldungen |
0 von maximal 24 |
| Literatur |
An Introduction to Statistical Learning with Applications in R (Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani).
Freely available at: http://faculty.marshall.usc.edu/gareth-james/ |