Data Analytics is one of the tracks of the Master's Econometrics. During your Master's you will follow 4 general courses and 5 track-specific courses and electives. You will finish with a thesis. If you have excellent analytical and leadership abilities and it is your goal to use applied research to tackle complex real-life problems, you can participate in our Honours programme. There is also an opportunity to pursue a Master’s degree in both Econometrics and Mathematics, if you opt for a Double Degree Master’s programme.
In this course, you will gain a deep understanding of econometric theory, practice and inference. You will learn how to apply advanced econometric techniques in practice, extend available methods for particular applications and how to implement them in a matrix programming environment. Also you will learn to understand and derive their statistical properties.
In this course, you will study the microeconomic theory of perfect and imperfect competition. Learn under what conditions markets perform well as a means to organise economic activity (and under what conditions they do not).
In this course, you will cover the basic theory of multivariate data analysis and of statistical methods in data science. You will focus on the most relevant multivariate techniques, as well as their application to econometric data in computer lab sessions. We will introduce you to Python, NumPy and pandas, data scraping, cleaning and wrangling.
In this course, you will build upon the general knowledge you acquired in Advanced Econometrics 1. You will gain a deep understanding of econometric theory, acquire the technical skills to conduct inference and be able to implement these techniques using software like MATLAB, R or Python.
In this course, you will learn to understand machine learning theory and apply your newly gained knowledge on large real-life datasets in computer lab sessions. You will be using software in Python.
In this course, you will discuss 8 recent empirical papers that apply microeconometric estimation techniques. These papers usually concern issues like individual choice behaviour in the labour and consumer markets. You will apply the techniques during the computer lab sessions with MatLab or R.
In this course, you learn about quantitative models for automated online marketing with large amounts of data. The topics we cover are today’s hot topics in automated online marketing. We discuss how techniques from statistics, econometrics, machine learning and OR are used for these real-world topics.
Choose 1 out of 2 electives:
Choose 1 out of 4 electives:
The academic programme culminates in a thesis, which allows you to engage with state-of-the-art data analysis and statistical techniques. The Master’s thesis is the final requirement for your graduation. It is your chance to dive deep into a topic in your field of choice (track) that you are enthusiastic about, and allows you to do an independent research project. A professor of your track will supervise and support you in writing your thesis.
If you are a student of the Master's Econometrics and you have a record of academic excellence, a critical mind and an enthusiasm for applied research, then our Econometrics Honours programme is a great opportunity for you.
If you want to pursue a Master’s degree in Econometrics as well as in Mathematics, you can opt for one of our Double Degree Master’s programmes:
I wanted to be an architect when I was a kid. Now I operate as a Machine Learning Engineer. The academic way of tackling a problem, something I learned during my studies, is something I still use a lot.Dolf Noordman - alumnus Master's Econometrics Read about Dolf's experiences with this Master's
One of the most essential problems in air traffic is delays of flights. They have important negative consequences in terms of costs, passenger demand, fares and airline reputation. Employ supervised machine learning techniques to predict the value of arrival delay in minutes. Combine historical flight details, weather conditions and aircraft characteristics of departing and arriving flights to find an optimal set of features by combining machine learning and econometric techniques.
Examples of relevant issues that could be discussed in your classroom.
Once you have completed your curriculum, you will have the possibility of doing an internship or going on an exchange abroad. For international students, it is an excellent opportunity to experience the Dutch labour market.
Are you interested in learning Dutch? There are various options available to maximise your Dutch experience and prepare for your future job in the Netherlands.
Many of our students are members of a study association. It is fun and useful for your future career at the same time. Faculty student associations are a great way to meet fellow students and future employers. They organise study trips (abroad), career events, weekly debates and social events. You can also purchase your textbooks and course syllabi at reduced rates.
Overview Study Associations
Amsterdam has a thriving student community with many activities organised outside of the university’s grounds. You will find student associations focusing on networking, specific interests and sports. It is only at sororities and fraternities that you can expect an initiation ritual (hazing).
At university, you are entitled to make your voice heard and assess the quality of your own education. Students can participate in the discussion on the university's education policy in various ways, such as by joining the Programme Committee, the Faculty Student Council or the first-year focus group. You can also stand for election and dedicate your efforts to the programme and your fellow students.
A specialisation track must be chosen when applying for the Master’s programme. However, track modifications are still possible until late October. The criteria for all tracks are identical and do not impact the likelihood of being accepted into the programme.
Our Master’s programme admits around 20 students per specialisation track. If you meet the entry requirements, you will always be accepted; this Master’s does not have a numerus fixus.
Most courses have one 2-3 hour lecture and one 2-hour tutorial per week. Generally students take 3 courses at a time, so count on about 12-15 contact hours per week.
Our preference is for in-person lectures. Certain sessions may be pre-recorded or follow a hybrid format. This entails preparing for Question and Answer (Q&A) sessions through video clips and readings, with subsequent online discussions during meetings.
Attendance is usually not compulsory for lectures, but commonly for tutorials and other sessions. Students greatly benefit from being present and engaging in discussions with both the instructor and their classmates.
The majority of courses have a written on-site exam, which counts for a large percentage of the final grade. Most courses have additional assessment methods, including oral presentations, developing research proposals, conducting experiments and writing up results. Finally, some courses grade attendance, which is reflected by presence and activity in tutorials and online assignments.