Data Science Methods for MADS
Faculteit | Economie en Bedrijfskunde |
Jaar | 2022/23 |
Vakcode | EBM216A05 |
Vaknaam | Data Science Methods for MADS |
Niveau(s) | master |
Voertaal | Engels |
Periode | semester I b |
ECTS | 5 |
Rooster | rooster |
Uitgebreide vaknaam | Data Science Methods for MADS | ||||||||
Leerdoelen | 1). Prepare raw marketing data for further analyses, based on knowledge of a selected number of data cleaning techniques. Understand the different characteristics of different types of data; 2). Explain and work with a selected number of computer science methods to analyze data. Understand how the methods work and apply in marketing tasks; 3). Evaluate existing applications of data science methods in marketing (those that are published in scientific journals and those that are used in practice) based on knowledge of earlier applications of these methods in marketing; 4). Manage, prepare and analyze data for investigating real-life marketing issues, using the techniques that are discussed in this course; 5). Translate the outcomes of the analyses into practical managerial implications. |
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Omschrijving | This course deals with data science methods for managing, preparing, and analyzing marketing data. The students learn from existing research, and are actively challenged to critique existing applications of data science methods. A significant part of the course is related to the actual implementation of these methods to a real-life marketing data in group assignments for which students will obtain assistance from the teacher during interactive tutorials. | ||||||||
Uren per week | |||||||||
Onderwijsvorm | -computer practicum, -hoorcollege , -werkcollege | ||||||||
Toetsvorm | -groepsopdracht, -schriftelijk tentamen (open vragen) | ||||||||
Vaksoort | master | ||||||||
Coördinator | dr. E. de Haan | ||||||||
Docent(en) | dr. E. de Haan | ||||||||
Verplichte literatuur |
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Entreevoorwaarden | The students are expected to have a basic knowledge of marketing management, and of quantitative techniques as regression models, ANOVA, hypothesis testing etc. Such knowledge can be simultaneously gained through concurrent modules as well. | ||||||||
Opmerkingen | Secretary Marketing (B. Wever): phone +31(0)50 3637065, e-mail: marketing.education@rug.nl, room 5411-0334 | ||||||||
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