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| Semester | Frühjahrsemester 2020 |
| Angebotsmuster | Jedes Frühjahrsem. |
| Dozierende | Dietmar Maringer (dietmar.maringer@unibas.ch, BeurteilerIn) |
| Inhalt | To counter-act the "data-rich, information-poor" ("drip") syndrome, this course covers concepts and techniques that aim at explorative analysis: finding structure within data, and, ideally, extracting information. These methods have their origins in areas such as machine learning, statistical learning, or data mining. These include (but are not limited to) non-linear regression methods, perceptrons and neural networks, support vector machines, tree-based methods, kernel-based methods, or rule-based methods. Typical applications are classification, prediction, clustering, or dimension reduction. Theoretical presentations are complemented with hands-on examples using the software package R and relevant toolboxes. Furthermore, we will discuss issues such as data preprocessing and data management. |
| Literatur | T. Hastie, R. Tibshirani, J. Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd ed., Springer 2009. E. Alpaydin, Introduction to Machine Learning, 2nd ed., MIT Press 2010. I.H. Witten, E. Frank, M.A. Hall, Data Mining: Practical Machine Learning Tools and Techniques, 3rd ed., Elsevier 2011. additional literature will be announced in the lectures |
| Weblink | Weblink on ADAM |
| Teilnahmebedingungen | completed BA in Business and Economics and following lecture: 12036 Econometrics |
| Anmeldung zur Lehrveranstaltung | Registration: Please enrol in MOnA. EUCOR-Students and students of other Swiss Universities have to enrol at the students administration office (studseksupport1@unibas.ch) within the official enrolment period. Enrolment = Registration for the exam! |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | Online-Angebot fakultativ |
| Intervall | Wochentag | Zeit | Raum |
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Keine Einzeltermine verfügbar, bitte informieren Sie sich direkt bei den Dozierenden.
| Module |
Modul: Kernbereich Wirtschaftswissenschaften (Masterstudium: Sustainable Development) Modul: Schadenversicherung (Masterstudium: Actuarial Science) Modul: Statistik und Computational Science (Masterstudium: Actuarial Science) Vertiefungsmodul: Marketing and Strategic Management (Masterstudium: Wirtschaftswissenschaften) Vertiefungsmodul: Quantitative Methods (Masterstudium: Wirtschaftswissenschaften) |
| Leistungsüberprüfung | Semesterendprüfung |
| Hinweise zur Leistungsüberprüfung | Active participation and engagement during the lectures; written assignments (upon agreement); and online exam: April 30, 8:00-9:00. Details will be communicated via emails. |
| An-/Abmeldung zur Leistungsüberprüfung | Anmeldung: Belegen |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,1 |
| Wiederholtes Belegen | beliebig wiederholbar |
| Zuständige Fakultät | Wirtschaftswissenschaftliche Fakultät / WWZ, studiendekanat-wwz@unibas.ch |
| Anbietende Organisationseinheit | Wirtschaftswissenschaftliche Fakultät / WWZ |