The specialization Econometrics and Data Science offers an excellent opportunity for those wishing to enhance their quantitative profile for a career in data science. The program combines different academic disciplines including statistics, econometrics, computer science, economics and business, but it is more than a simple intersection of these. In essence, it is concerned with the theory and practice of transforming large and complex data sets into pieces of information that are potentially beneficial for a wide range of purposes relevant to corporates, economic and government institutions, and financial service companies.

Admission requirements The track Econometrics of the Master's 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. Mathematics: 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. Probability: 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. Mathematical Statistics: Statistical Inference, George Casella and Roger L. Berger, Cengage Learning, 2008. Introductory Econometrics 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. Intermediate Econometrics A Guide To Modern Econometrics, Marco Verbeek, Wiley, 5th Edition, 2017. Basic skills in Computer Programming in Python, R, Matlab, Ox or Java. If you can show certified exam results for courses that are related to the subjects and are of a comparable level (each course with a workload of 6 EC or close to it), this is satisfactory. The equivalence will be evaluated by the Examination Board and its approval determines the admission. English language proficiency The admission board wants to stress the intensity of the programme: reading scientific articles and writing papers will be a key part, all in a very high pace. Your English language skills, both oral and written, are extremely important in this programme. As you will have to communicate frequently with your fellow students and you will be working with and for international companies. VU Amsterdam requires all applicants to take an English test. You can already apply online without having the test results. We do advise you to plan a test date as soon as possible. Below you will find the minimum English test scores for the programme: IELTS (academic): • Minimum general score 6,5 • Minimum score speaking 6,5 • Minimum score listening 6,5 • Minimum score writing 6,0 • Minimum score reading 6,0 TOEFL: • Paper based test 580 • Internet based test 92-93 Cambridge English: • Cambridge Proficiency Exam A, B, C • Cambridge Advanced Exam A, B, C