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Econometrics: Data Science & Business Analytics (track)

Study programme

Econometrics: Data Science & Business Analytics (track)

Programme: common part

The common programme in brief of the MSc in Econometrics (60 ec) consists of the four courses (20 ec in total):

  • Advanced Econometrics I (semester 1, blocks 1+2): this course discusses up to date econometric techniques to analyse economic data;
  • Theory of Markets (semester 1, block 1): this course is on the analysis of markets using advanced mathematical tools;
  • Data Science Methods (semester 1, block 1): this course provides insight in processing and analysis large quantities of information (big data);
  • Advanced Econometrics II (semester 1, block 3): this course discusses relevant topics in modern economentrics.

After the first period of semester 1, students choose two out of three of the courses:

  • Complex Economic Dynamics;
  • Financial Mathematics for Insurance (6 EC);
  • Machine Learning for Econometrics.

This choice restricts track choices from four to three because Complex Economic Dynamics is mandatory in the Complexity and Economic Behaviour track, Financial Mathematics is compulsory in the Financial Econometrics track and Machine Learning is compulsory in the Data Science and Business Analytics track.

The semester 2 courses are all track specific. Information on these courses can be found below.

To fully grasp the new phenomenon of Big Data, the Data Science & 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. 

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 Data Science & Business Analytics. 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. 

Programme structure

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. 

First semester

30 EC will come from courses as described above. It is mandatory to choose Machine Learning for Econometrics.

Second semester

The students of this track take the following courses:

  • Microeconometrics (5 EC, semester 2, block 1)
  • Quantitative Marketing (5 EC, semester 2, blocks 1+2);
  • An elective from the list below;
  • 15 EC master thesis on data science and business analytics.

Course Catalogue

Data Science & Business Analytics: Electives

  • Economic and Financial Network Analysis;
  • Information Visualisation (FNWI-course);
  • Any other course on Data Science, Big Data or Business Analytics course if approved by the programme director.

Thesis

Your Master’s thesis is your graduation piece of work and it will be supervised by one of the researchers in Department of Quantitative Economics. Your thesis must add to the existing body of scientific knowledge to an appropriate extent and it may be written during an internship at a firm.