The Big Data Business Analytics track of the Master’s in Econometrics programme is designed with the help of leading Big Data companies to connect one of the most promising developments in today's business with the econometrics curriculum. Unravel and interpret correlations among the petabytes of complex data generated every day by social media and the internet in general.
- Prepare for a career as a Big Data specialist in the economics and business environment;
- acquire a deep insight into developments that are revolutionising today's economy;
- become an expert in a new field that taps into the surge of consumer data.
The programme in brief
To fully grasp the new phenomenon of Big Data, the Big Data Business Analytics track provides you with the skills, expertise and techniques that are required to apply robust statistical methods, to be used in exploring all topics, research and issues relevant to the discipline. Study the correlations between data flows for predictive purposes and apply game theory to social media and the internet. The multidisciplinary character of the programme is reflected in the wide range of courses you can take, such as: General Equilibrium Theory, Micro-Econometrics, Financial Mathematics for Insurance, and Quantitative Marketing.
Many of the lecturers in the programme are researchers at one of the ten research programmes of UvA Economics and Business. Benefit from a programme that covers both the knowledge and skills required for practitioners and for a career in research – designed in cooperation with leading specialists in Big Data. The ASE’s affiliation with a number of internal and external economics-related research institutes enriches the research and career opportunities for students in the Master’s programme.
The Big Data Business Analytics track of the master Econometrics is a one-year programme of 60 ECTS credits (1 ECTS credit = 0.5 US credits). The academic year runs from September to the middle of July and is divided into two semesters, each with three periods. Refer to the academic calendar for exact dates.
The curriculum for the Master’s in Econometrics is quite demanding, with classes taking up 12-15 hours a week on average. An additional 25 hours are required for class preparation, homework, debates, casework and computer time.
In the first semester, you'll be given a solid basis in econometrics with several core courses for students of all tracks. General Equilibrium Theory teaches you to formulate the general equilibrium model and understand its basic properties, and critically evaluate underlying model assumptions and implications. Through Advanced Econometrics 1 and 2, you’ll obtain a deep understanding of econometric theory, practice and inference by using a variety of advanced techniques.
The theoretical background and economic applications of Game Theory trains you in the ability to model interactive decision-making situations using game-theoretic techniques, and compute and characterise their equilibrium outcomes.
You'll also take one elective and one track-defining course, Machine Learning for Econometrics. Understand the principles of machine learning at an advanced level and acquire the skills to apply machine learning to complex problems in the real world.
During the first part of the second semester, you'll focus on your specialisation track in three electives. In the track-defining course Quantitative Marketing, you analyse relevant marketing questions and learn to apply quantitative techniques for making data driven marketing decisions. Financial Econometrics covers topics such as non-linear time series, volatility models, and the pricing of complex derivatives.
For your electives, you have a wide range of options. Study operations research, for example, or privacy law and ethics. Part two of the semester will be spent on completing a thesis in one of four specialised areas of expertise. A research staff member from the Department of Quantitative Economics will supervise your work.
This school offers programs in:
Last updated November 30, 2017