Marketing Data Science is a specialization of the Econometrics and Operations Research master's programme. This hands-on study into econometric methods for analyzing marketing data to facilitate better marketing strategies let you become the quantitative marketing specialist and place you at the forefront of a successful professional career.
Marketing Data Science connects many academic disciplines including mathematics, statistics, economics, and marketing, and is primarily concerned with the use of micro economics, consumer behaviour and statistical techniques to analyse data sets with multiple hierarchies such as product, brand, location, distribution, etc. The econometric methods can be used to analyse volume shares, advertising effects, sale strategies, consumer behaviour, brand loyalty schemes, TV and social media advertising, and many other topics.
We welcome motivated and ambitious students who are interested in advancing their knowledge in Econometrics and related subjects, and are aware of their role in society. In order to be successful in this programme you will need a solid basis in mathematics, statistics and econometrics. In particular, we expect that you have passed courses in mathematics (calculus, analysis), probability, Mathematical statistics, and econometrics. A basic knowledge in computer programming is also required.
The track Econometrics of the Master programme Econometrics and Operations Research, with specializations Econometric Theory, Financial Econometrics, Empirical Marketing, and Quantitative Economics, is open to students with a university Bachelor's degree that provides a thorough knowledge in mathematics (analysis, calculus), probability, (mathematical) statistics, econometrics and computer programming. You need to have successfully completed courses and studied literature related to the core of this programme, which is based on the following books.
- Calculus Early Transcendentals, James Stewart, Cengage Learning, International Metric Edition - 7th Edition, 2011.
- Linear Algebra and its Applications, David C. Lay, Steven R. Lay and Judi J. McDonald, Pearson Education, 5th Edition, 2016.
- A First Course in Probability, Seldon M. Ross, Pearson Education, 9th Edition, 2013.
- Fundamentals of Probability, with stochastic processes, Saeed Ghahramani, CRC Press, Taylor and Francis Group, 3rd Edition, 2016.
- Statistical Inference, George Casella and Roger L. Berger, Cengage Learning, 2008.
- Introduction to Econometrics, James H. Stock and Mark W. Watson, Pearson Education, 3rd Edition, 2014.
- Introductory Econometrics: A Modern Approach, Jeffrey M. Wooldridge, Cengage Learning, 2013.
- A Guide To Modern Econometrics, Marco Verbeek, Wiley, 5th Edition, 2017.
Basic skills in Computer Programming in Python, R, Matlab, Ox or Java.
In most cases, approval is given to students who have completed:
- a Bachelor's programme in Econometrics and Operations Research at a Dutch university
- the VU SBE Minor programme Applied Econometrics: A Big Data Experience for All, 30 EC (5 x 6 EC courses) with a GPA of at least 7.5 — PLUS two VU SBE Bachelor third year courses in Econometrics
- the VU SBE deficiency programme Econometrics
To enroll in the programme submit your enrolment application via Studielink.
Please note: in Studielink you can apply for the Master in Econometrics and Operations Research and in VUnet you can select the specialization Econometrics.
Apply for the programme MSc Econometrics and Operations Research via Studielink. You can register for the specialization Econometrics in VUnet (see step 2)
After application in studielink you will receive a VUnet-ID and password. Please complete your application in VUnet by answering additional questions, affirming your choice for the specialization Econometrics and uploading the following document:
- a formal transcript of your bachelor grades. Your transcript must include an average score (GPA).
Please note: we can only process your application when your choice of specialization is clear and you uploaded your transcript.
The admission committee will assess if you meet the admission criteria and will inform you about the decision via email.
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Three core 6 EC courses (compulsory):
• Advanced Econometrics
• Multivairate Econometrics
• Time Series Models
Five specialization courses (of which one is compulsory and 2 or 3 elective):
• Marketing Strategy
• Large Scale Data Engineering
• Web Data Processing Systems
• Branding and Advertising
• Marketing Data Case (compulsory)
One elective 6 EC course (or additional specialization course):
• Digital Marketing and Technology
• Geographic Information Systems
• Regional and Urban Economics
• Transport Economics
• Big Data Analytics in Geographic Information Systems
• Big Data Analytics
• Data Mining Techniques
Thesis (18 EC): an in-depth study on a challenging topic in econometrics with emphasis on theory, methodology or computing.
Computer Programming Bootcamp
Annual schedule 2019-2020
PhD student, Customer Intelligence analyst, Quantitative analyst, Marketing Modeler, Consultant Data Analytics, Statistical researcher, Quantitative marketing analyst, Quantitative researcher, Data analyst, Quantitative methods instructor, Data scientist, Sales Management consultant, Statistician, Quant Sales analyst, and many more.
About this institute
Welcome to Vrije Universiteit Amsterdam
Vrije Universiteit Amsterdam (‘VU Amsterdam’) is an internationally renowned research university founded in 1880. The university offers over 170 English-taught programmes at Bachelor’s, Master’s and PhD level to more than 24,000 students from all over the world. Students and staff...
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