The first 2 academic years of the BSc Econometrics and Data Science are in common with the Bachelor's programme in Actuarial Science. After the 2nd year you specialise in either Econometrics or Data Science.
In this course you learn about important macroeconomic concepts that help analyse how the economy interacts with changes in government purchases, taxes, or money supply. With this knowledge, you’ll interpret events in macroeconomic history since WWII, especially through illustrations in lecture and tutorial groups.
This course is an introduction to calculus at the academic level. You learn about basic topics from classical differential calculus and integration theory. The working classes will help you deepen theoretical insights through exercises and further applications.
In this course you learn to explain basic microeconomic concepts, how to model markets and behaviour, and perform a basic (mathematical) analysis of these. You also search academic sources to write a literature review on a microeconomic topic.
This course gives you a solid basis of probability theory and descriptive statistics, which provides you with an indispensable basis for many subsequent courses in the programme. In the lectures you will do theory, in the tutorials exercises with applications.
This course teaches you the basics of Econometrics and of general topics in the fields of Actuarial Science During computer lab sessions you learn how to implement calculations and will conduct a research project using R.
This course is your introduction into modern finance. Central topics are the assessment and financing of investment projects. You also get acquainted with the fundamental relationship between risk and return by learning about modern portfolio theory and the capital asset pricing model (CAPM).
This course provides you with a solid basis of linear (matrix) algebra as indispensable knowledge for the remaining study in Econometrics and Actuarial science. You practice the theory through exercises and will also learn how to use computer software (R) to solve larger problems.
In this course we advance on the single variable distributions and focus on multivariate probabilistic models. You will learn the basics of hypothesis testing. Both approaches are at the core of econometric analysis. R will be used for coding.
This course provides you with a solid basis of computer programming and numerical analysis, both indispensable skills in the fields of Econometrics and Actuarial Science. You develop so-called algorithmic thinking to design algorithms and translate these into computer language (R and Python).
This course covers the basics of how and when to perform data preprocessing. This essential step in any machine learning project is when you get your data ready for modelling with help of Python. Also, part of this course is the (preparation of) a presentation of a related scientific subject.
In this course you learn about the models and calculations used by actuaries for valuing, pricing, and reserving in a life insurance and pension fund context.
This course advances on Mathematics 2. You will learn about eigenvalues, orthogonalization, different matrix decompositions and applications in optimisation (quadratic forms). This theory will be valuable for data analysis later. You will use Python for calculations.
Multivariate analysis involves evaluating multiple variables to identify any possible association among them. In this course you learn about several advanced concepts in nonlinear analysis and how to apply them to solve small problems analytically, and large problems numerically (using Python).
In this advanced course in mathematical statistics you learn about several convergence notions for distributions and estimators. This is used to derive confidence intervals and statistical tests and their elementary properties. You learn how to derive generalized likelihood ratio tests. R is used for necessary coding.
The main idea in statistical learning theory is to build a model that can draw conclusions from data and make predictions. In this introductory-level course, you learn about its fundamental issues and challenges and will discuss popular statistical (machine) learning approaches.
In this course, you will learn how to set up proper models to quantify the relationship between (economic) variables using tools from linear algebra and mathematical statistics. You explore and learn how to apply the so-called multiple regression model.
In this course, you will study determinants of small scale economic environments using a model-based approach. Using multivariate analysis, you will learn about both consumer behaviour (choice and risk attitude) and firm behaviour (types of competition). Special attention goes out to general equilibrium and game theory.
In this course, you learn about a number of fundamental concepts that are important for the interpretation of quantitative results. It also provides you with initial techniques and extensions for correct modelling of economic variables.
During this course, you apply the knowledge you acquired during this bachelor in practice. We discuss scientific articles and the underlying theory, and critically evaluate assumptions and techniques. You work on a group research project, with individual presentation of the results.
In the 1st semester you can choose from several options: Minor programme, or Studying abroad, or Company Internship in combination with Electives, or Electives.
Time series analysis covers methods for analysing and forecasting data with temporal patterns. Topics in this course include time series models, seasonality, trend detection, and statistical techniques. We also explore practical applications in both finance and economics.
Reinforcement learning is an autonomous, self-teaching system that helps determine if an algorithm is producing a correct right answer or a reward indicating it was a good decision. In this introductory-level course we discuss different models (dynamical programming, SARSA and Q-learning models) and apply them using software (like Python).
You will familiarise yourself with advanced model-based concepts of industrial organisation. You will study for market structure and behaviour and the role of competition policy, using game theoretic concepts. Some keywords are: Cournot, Bertrand and Stackelberg competition, anticompetitive behaviour, mergers, tacit collusion, repeated games.
Time series analysis covers methods for analysing and forecasting data with temporal patterns. Topics in this course include time series models, seasonality, trend detection, and statistical techniques. We also explore practical applications in both finance and economics.
Is there a recent development or business idea that sparks your enthusiasm? While writing your thesis, you have the chance to explore it while simultaneously training your ability to independently conduct relevant and valuable research.
Expanding your knowledge and at the same time developing your skills is key. That is why you will participate in a variety of teaching activities. Most of the courses are evaluated with one or more tests. This is usually a written examination, but it can also be an essay, a report, or a presentation.
Lectures (8 hours)
Lectures give an introductory overview into the course content. You will attend them together with your fellow students. You take notes and have the opportunity to ask questions.
Also, you can expect guest lectures from experts working in a wide range of economic organisations and fields.
Seminars (6 hours)
During seminars you will discuss specific subjects from the lectures in smaller groups. Exercises and practice assignments will help you to become adept with the theory. There are two types of seminars, those with plenary sessions and the small scale groups where you will work individually.
Practicals (2 hours)
During practicals you learn how to work with various mathematical and statistical computer programmes.
Self-study (20 hours)
During your study week, you spend time to study theory, go over lectures and seminars, and prepare for exams and presentations.
This year is all about your basic knowledge of mathematics, information science, probability theory, statistics and economics.
The 2nd year enhances your mathematical, statistical and research skills. You will start to apply these tools to econometrics and data science. You will take mandatory courses like Mathematical Economics, Econometrics 1&2 and Statistical Learning.
In year 3 you will specialise and choose one of the 2 specialisations:
My Semester: customise your programme
In the 3rd year you are offered the opportunity to design your own programme in the 1st semester. You can choose from a number of options:
Study a semester abroad; participate in the UvA Exchange programme.
There is some coursework in semester 2 of year 3, but a large part will be devoted to conducting and reporting on your own research. Is there a particular recent development that sparks your enthusiasm or do you have a great idea of your own? Writing your thesis, you have the chance to explore it fully while simultaneously training your ability to independently conduct relevant research.
Your thesis is the final requirement to be completed for your graduation. Under the supervision of our researchers, you will follow a clearly defined path that will lead to your graduation with a Bachelor's degree.
The transition from secondary school to university can be a major step. For this reason, you will receive intensive academic counselling as a 1st year student.
In the 1st semester 2 hours per week are scheduled as Skills & Connect to let you adjust to the new environment. You will learn about studying strategies, time management, and also get help with basic math & stats skills.
You can also count on individual support during the rest of your studies. Support is offered through our team of experienced student counsellors.
At UvA there are all sorts of activities you can undertake during your university years to explore and develop your network, talents and skills.
If you are ambitious, you can choose to take part in our Honours programme. You take the Honours programme alongside your regular studies. Completion results in you graduating 'with honours': an internationally recognised qualification.
During your Bachelor's programme, you could put your knowledge into practice by means of a work placement. Internships can be very useful for your future career.
Studying abroad allows you to get to know a different culture, language and country, and we strongly recommend you take advantage of this opportunity. We have made collaborative and exchange agreements with over a 100 universities abroad, enabling you to study there for a semester.
Are you interested in learning Dutch? There are different options to give you the opportunity 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, parties and receptions with drinks. Sometimes 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.
The availability of satellite imagery makes it possible to estimate crop yields on the basis of weather conditions and crop growth. Machine learning techniques are used to transform the imagery to useful data, that would be hard to get otherwise. In this way particularly vulnerable populations can be identified, and help by NGO’s like the WFP can be effectively targeted. In the 2nd year of your Bachelor’s you will learn how to identify relevant characteristics in various data resources, and how to use these to make reliable estimates and predictions.
In this Bachelor's programme, you’ll learn how to use mathematics, probability and statistics to quantify (financial) risks and solve problems in society or the business world. Social issues increasingly play a role in this. The study programme therefore regularly covers topics such as sustainability, ethics and social responsibility. For example, you will learn how to research how many people choose more sustainable ways of travelling if fuel excise duty is increased.
Through practical assignments, you will directly apply the knowledge you acquire during your studies to current topics in the media and real business cases. These topics are often related to ethics, corporate social responsibility and/or sustainability. This starts in the 1st year in Introduction Econometrics and Actuarial Science and Introduction Data Science. Furthermore, there is an explicit focus on ERS themes in courses such as Mathematical Economics 1 and 2, Econometrics 1 and 2, and Empirical Project.
Throughout this 3-year programme, themes related to sustainability, ethics and corporate social responsibility will remain important topics.
Data analysis, programming and statistics suit me down to the ground. It's like doing extremely advanced puzzles. You can get stuck sometimes, but once I find that solution, I'm over the moon.Liselotte Siteur, student Econometrics and Data Science Read about Liselotte's experiences with this Bachelor's
In both Econometrics and Data Science and Actuarial Science, mathematics, statistics, and economics have focus. Econometrics and Data Science is concerned with analysing and making sense of economic relationships from a broader perspective. Goal is to help organisations in making better business and policy decisions. Actuarial Science is more about understanding and managing financial risks, especially in insurance and finance.
This Bachelor’s programmes is very focused on mathematics. Therefore it is an advantage if mathematics is one of your favourite subjects and you excel in it. If you want to know which level of math is required, please take a look at the entry requirements.
You don't need any programming skills before you start Econometrics and Data Science or Actuarial Science. You will learn everything you need to know in terms of programming during the Bachelor's.
No, there are no differences.
The first 2 years of the programmes are nearly identical. Therefore it is possible to switch between the two programmes until the end of the 2nd year. Depending on the time of your switch, you may need to take an extra course to comply with the requirements of your new programme.
To make the transition from secondary school to university as easy as possible, you will receive extra guidance in the 1st year and will be assigned a tutor. This tutor will introduce you to both the campus and the city of Amsterdam, so you will quickly feel at home. This senior student will also give you tips on how to study smart and you can discuss your study goals and progress. Also during the rest of your studies you can count on support from our study advisers, mentors, tutors and our Economics and Business Career Centre. You can contact our experienced student advisers for questions about your Bachelor's programme, study planning or personal circumstances that may affect your studies.