Courses Exchange Display 2021-2022
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| Course title | Business Intelligence Case Studies | |||||||||||||||||||||||||||||||||||||||
| Course code | EBC4107 | |||||||||||||||||||||||||||||||||||||||
| ECTS credits | 6,5 | |||||||||||||||||||||||||||||||||||||||
| Assessment | Whole/Half Grades | |||||||||||||||||||||||||||||||||||||||
| Period |
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| Level | Advanced | |||||||||||||||||||||||||||||||||||||||
| Coordinator |
Roberto Cerina For more information: r.cerina@maastrichtuniversity.nl |
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| Language of instruction | English | |||||||||||||||||||||||||||||||||||||||
| Goals |
This course aims at getting hands-on experience in analysing managerial decision processes based on available data from real-life cases.
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| Description |
This course treats the theory and practice of Business Intelligence. Tools for the analysis of data are discussed, as well as methods for discovering knowledge from information and using this knowledge for intelligent decision making.
Methods for the analysis of data are presented, from current data mining toolboxes. We study how (and how not) to build predictive models to extract information from large data bases and how to interpret the more efficiently and to develop new services for the organizations that provide the data. The course consists of applying up-to-data data mining techniques on real-life problems. These techniques will be implemented with modern software tools (SAS, SPSS modeler, Tableau, WEKA, XLMiner). Cases are selected from the literature and our own research experience. |
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| Literature |
* Data Science for Business, What You Need to Know about Data Mining and Data-Analytic Thinking, by Foster Provost and Tom Fawcett, O' Reilly Media 2013, ISBN 978-1-4493-6132-7, EBook ISBN 978-1-4493-6131-0.
* Other materials, i.e. articles, will be made available through Student Portal. |
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| Prerequisites |
Basic statistics.
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| Teaching methods (indicative; course manual is definitive) | PBL / Presentation / Lecture / Assignment / Groupwork | |||||||||||||||||||||||||||||||||||||||
| Assessment methods (indicative; course manual is definitive) | Final Paper / Participation / Presentation | |||||||||||||||||||||||||||||||||||||||
| Evaluation in previous academic year | For the complete evaluation of this course please click "here" | |||||||||||||||||||||||||||||||||||||||
| This course belongs to the following programmes / specialisations |
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