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| Semester | spring semester 2018 |
| Course frequency | Every spring sem. |
| Lecturers | Dietmar Maringer (dietmar.maringer@unibas.ch, Assessor) |
| Content | 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. |
| Bibliography | 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 |
| Admission requirements | completed BA in Business and Economics and following lecture: 12036 Econometrics |
| Course application | Registration: Please enrol in MOnA. Enrolment = Registration for the exam! |
| Language of instruction | English |
| Use of digital media | Online, optional |
| Course auditors welcome |
| Interval | Weekday | Time | Room |
|---|
No dates available. Please contact the lecturer.
| Modules |
Module: Core Competences in Economics (Master's Studies: Sustainable Development) Non-Life Insurance Module (Master's Studies: Actuarial Science) Specialization Module: Marketing and Strategic Management (Master Business and Economics) Specialization Module: Quantitative Methods (Master Business and Economics) Statistics and Computational Science Module (Master's Studies: Actuarial Science) |
| Assessment format | end-of-semester examination |
| Assessment details | Active participation and engagement during the lectures; written assignments (upon agreement); and written exam: 10.04.18; 12:15-13:15. You can still withdraw from the examination by submitting a completed, signed form to our office from 27.03.18 until 06.04.18 / 12:00 o’clock. Withdrawals sent by email will not be accepted. You will find the examination withdrawal form on the Homepage of the Student Dean’s Office. Prior to 26.03.18, please only use MONA for withdrawing. The exam rooms will be published up to 25.05.18. |
| Assessment registration/deregistration | Registration: course registration |
| Repeat examination | no repeat examination |
| Scale | 1-6 0,1 |
| Repeated registration | as often as necessary |
| Responsible faculty | Faculty of Business and Economics , studiendekanat-wwz@unibas.ch |
| Offered by | Faculty of Business and Economics |