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In the Econometrics and Data Science Bachelor’s we train you to use mathematical and statistical methods to help solve problems in society or in the business world. With your expertise, you can advise organisations on the effect of their strategies and business operations. Or help businesses use extensive data analysis to shape their strategies. You will examine case studies and learn to work with advanced software. After the 2nd year, you can choose between 2 specialisations: Econometrics or Data Science.

The programme

The first 2 academic years of the Bachelor's 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.

Dutch or English?

If you are a Dutch-speaking student, you can also opt for our Dutch track. Both programmes are identical in terms of level and content. If you’re looking for a smoother transition to a fully English-taught programme, the Dutch track could be the right choice for you.

COURSES SEM 1 SEM 2 SEMESTER 1 SEMESTER 2 EC
  • Macroeconomics for AE
    Period 1
    6

    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 will interpret events in macroeconomic history since WWII, especially through illustrations in lecture and tutorial groups.

  • Mathematics 1: Calculus
    Period 1
    6

    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.

  • Microeconomics for AE
    Period 2
    6

    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.

  • Probability Theory and Statistics 1
    Period 2
    6

    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.

  • Programming and Numerical Analysis
    Period 3
    6

    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).

  • Finance for AE
    Period 4
    6

    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).

  • Mathematics 2: Linear Algebra
    Period 4
    6

    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.

  • Introduction Econometrics and Actuarial Science
    Period 5
    6

    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.

  • Probability Theory and Statistics 2
    Period 5
    6

    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.

  • Introduction Data Science: Data Preprocessing
    Period 6
    6

    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.

COURSES SEM 1 SEM 2 SEMESTER 1 SEMESTER 2 EC
  • Life Insurance Mathematics
    Period 1
    6

    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.

  • Mathematics 3: Advanced Linear Algebra and Real Analysis
    Period 1
    6

    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.

  • Mathematics 4: Multivariate Analysis
    Period 2
    6

    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).

  • Probability Theory and Statistics 3
    Period 2
    6

    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.

  • Statistical Learning
    Period 3
    6

    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.

  • Econometrics 1
    Period 4
    6

    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.

  • Mathematical Economics 1
    Period 4
    6

    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.

  • Econometrics 2
    Period 5
    6

    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.

  • Empirical Project
    Period 6
    6

    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.

  • Restricted-choice electives
    Period 5
    6
COURSES SEM 1 SEM 2 SEMESTER 1 SEMESTER 2 EC
  • Free-choice electives: Minor's programme/Studying abroad/Company Internship/Electives
    Period 1
    Period 2
    Period 3
    30

    In the 1st semester you can choose from several options: Minor programme, or Studying abroad, or Company Internship in combination with Electives, or Electives.

  • Specialisation Data Science: Text Retrieval and Mining
    Period 4
    6
  • Specialisation Data Science: Time Series Analysis
    Period 4
    6

    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.

  • Specialisation Data Science: Reinforcement Learning
    Period 5
    6

    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).

  • Specialisation Econometrics: Mathematical Economics 2
    Period 4
    6

    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.

  • Specialisation Econometrics: Time Series Analysis
    Period 4
    6

    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.

  • Specialisation Econometrics: Microeconometrics
    Period 5
    6
  • Bachelor's Thesis and Thesis Seminar
    Period 5
    Period 6
    12

    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.

Compulsory course
Elective
Specialisation
  • Your study week

    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.
    • Tutorials (6 hours): During tutorials, 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.
    • Skills & Connect: In the first 6 months of your studies, you will receive weekly coaching from a senior student in a small group. This mentor will help you learn to study more effectively and you will work together on your basic mathematics and statistics skills. In the meantime, you will also get to know your fellow students.
  • Year 1: develop a solid foundation and get to know the specialisations

    This year is all about your basic knowledge of mathematics, information science, probability theory, statistics and economics. You will apply this knowledge of mathematics and statistics to economics subjects, such as:

    • Macroeconomics: how does the economic system function in general.
    • Microeconomics: how businesses and consumers behave in a market.
    • Finance: what does a business structure look like and how are investments made.

    In the 2nd half of year 1 you will be introduced to the specialisations: Econometrics and Data Science (of the Bachelor's programme in Econometrics and Data Science) and Actuarial Science (of the Bachelor's programme in Actuarial Science) - in the first 2 years of both studies you follow almost the same programme.

    • In the course Introduction Econometrics and Actuarial Science, you will use advanced mathematical and statistical programming software such as 'R' and 'Python' to make your first predictions and analyses based on data.
    • In the final course Introduction Data Science, you will learn how to deal with large collections of data. You will learn how to use software to prepare, or structure and clean, data for analysis. A dataset is often much too large to analyse directly, so you will learn different compression techniques that are applied to video and sound on platforms such as YouTube, TikTok and Instagram. Focus is on how to obtain the relevant characteristics (features) of your data.
  • Year 2: extend the foundation

    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 and Econometrics 1&2. The focus here is on making predictions using models that incorporate observed data.
    • In the course Statistical Learning, you will explore various machine learning techniques frequently used in artificial intelligence. By the end of this year, you will understand the fundamental concepts behind automatic email spam filtering, financial fraud detection, and how individuals' creditworthiness is assessed based on various financial and demographic data. You will also examine the ethical implications of such analyses, including how to avoid embedding unwanted discriminatory biases in your data models.
    • In the final course Empirical Project, you will apply all your knowledge from the econometrics courses in a group project. You will assess the reproducibility of past research by, for instance, investigating the causal relationship between a country's economic growth and its colonial past, all through data analysis.

    By the end of year 2, you will be capable of independently conducting a data analysis project. You will have sufficient knowledge of statistics, machine learning, and econometrics to utilise various methods and apply them according to the research question.

  • Year 3: extend your knowledge and specialise

    In year 3 you construct your own programme in the 1st semester. In the 2nd semester, you will specialise in one of the 2 specialisations.

    1st semester (My semester: customise your programme)

    Your 3rd year is all about exploring your individual academic interests. The 1st semester of this year is all yours to construct. Options include an internship, studying abroad or free-choice electives.

    • Do an internship: work at a company where you can put the experience and skills that you have gained into practice.
    • Study abroad: spend a semester studying at one of our many partner universities to give you an exciting experience.
    • Take a minor programme at the UvA or elsewhere: this gives you a chance to broaden and differentiate your knowledge. Minors that our students often choose, include: Programming, Mathematical Topics, and Macroeconomics. The selected minor should be relevant to your specialisation and offer a valuable contribution to it.
    • Deepen your knowledge with electives: choose between specialised courses in the area of business and economics to deepen your business knowledge.

    2nd semester: Specialisation

    In the 2nd semester, you will specialise by choosing one of two specialisations:

    1. Econometrics
      If the government increases excise duties to raise the price of petrol, fewer people will use their cars. By modelling reality, econometricians attempt to prove such statements. These econometric models are used to forecast the economy and make recommendations on economic policy. In this specialisation, you will learn how to develop and use economic models to analyse economic problems and provide policy recommendations. Courses in this specialisation include:
      • Mathematics Economics 2: How do markets and firms operate within the economy, and what policy tools can the government use to steer market operations?
      • Microeconometrics: Learn to analyse large datasets on individuals and households using modern techniques. What patterns of economic behaviour can be identified? This is an application-oriented course where you integrate knowledge from previous econometrics courses.
         
    2. Data Science
      In Data Science, the focus is more on making predictions and less on analysing the processes behind a problem. You will concentrate more on programming and fine-tuning tools than on the statistical background of the models. Nowadays, firms collect enormous amounts of data ('big data'), creating a significant demand for data scientists. This data contains valuable information to improve sales and profits. Consequently, the emphasis is more on programming and fine-tuning tools than on the statistical background of the methods. Machine learning and AI are at the core of this specialisation. Courses in this specialisation include:
      • Text Retrieval and Mining: How can you apply computer science and machine learning to automate tasks humans perform on collections of texts? For instance, automatically grouping news articles by topic, detecting plagiarism, or identifying sentiment related to an event or brand.
      • Reinforcement Learning: In Reinforcement Learning, computers learn to make the best decisions through interaction with their environment. Instead of receiving explicit instructions, they learn through trial and experience. This is particularly useful for robots, autonomous vehicles, and playing games.

     

  • Thesis

    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.

Additional options during your studies
  • Dutch or English

    This Bachelor’s offers a Dutch and an English track. If you are a Dutch-speaking student, you can choose to follow our Dutch track. Both tracks are identical in terms of level and content.

    Dutch track

    In the Dutch track, tutorials and some lectures will be conducted in Dutch. You will also complete assignments and exams in Dutch. Each year, the amount of English used in the programme gradually increases, ensuring you a smooth transition to a fully English-taught programme. The Dutch track can be a good choice if you want some time to adjust to the English language and prefer a gradual transition to a fully English-language programme.

    English track

    If you opt for the English track, all courses are in English. From year 1 you will study with both Dutch students and students from around the world. This creates a diverse and international classroom.

  • Student coaching

    The transition from secondary school to university can be a major step. For this reason, you will receive intensive academic counselling as a 1-year student. You can also count on individual support during the rest of your studies.

  • Minors and electives

    The UvA offers a variety of minors and a wide selection of elective courses that you can undertake during your university years to broaden or deepen your knowledge.

  • Honours programme

    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.

  • Internships

    During your Bachelor's programme, you could put your knowledge into practice by means of a work placement.

  • Studying a semester abroad

    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.

  • Dutch language course

    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.

  • Study associations

    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.

    The VSAE is the primary study association for the ‘quant' within the economics department, i.e., students Econometrics and Data Science, Actuarial Science and Business Analytics. Through a membership you can purchase your textbooks and course syllabi at reduced rates. But there are other associations as well.

  • Student 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).

  • Student participation

    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 student panel. You can also stand for election and dedicate your efforts to the programme and your fellow students.

Experience the study

Real-life case: battle against hunger and poverty

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.

Responsibility, sustainability and ethics integrated to the curriculum

In this Bachelor's programme, you will 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. Sustainability also plays a significant role in the insurance industry. Due to climate change, weather conditions are becoming more extreme, leading to damages in many areas. It has become a relevant issue to use data to estimate which damages can be insured and what the corresponding premiums should be. There may also be uninsurable risks that can motivate policyholders to operate more sustainably. Data specialists often work with personal data, where privacy issues almost inevitably come into play. Ethics also come into focus, for example, when ethnic background should not be considered in the research. The challenge here is to process the data in advance to avoid unwanted biases.

How are these themes integrated into the curriculum?
  • Year 1

    Sustainability, ethics, and corporate social responsibility are introduced right from the 1st year in courses like Introduction to Econometrics and Actuarial Science, and Introduction to Data Science. In Mathematical Economics 1, you will encounter issues related to the distribution of resources in the economy. In Econometrics 1 & 2 and the Empirical Project, you will explore research in these themes. In the elective course International Partnerships for Local Global Challenges, in the first semester of the 3d year, you will take on the challenge of working with students abroad to address a societal issue, with a particular focus on these themes.

  • Year 2

    In the 2nd year course Introduction to Machine Learning, you will  learn how to mitigate unwanted biases in your research design. Climate change has become more of a concern for insurance companies, as policyholders face more frequent and severe damages due to extreme weather events. You will delve deeper into this in the course Risk Theory, where you'll explore whether risks can be insured and, if so, what premiums insurers should charge to continue covering the damages.

Throughout this 3-year bachelor's programme, you will directly apply the knowledge gained during your studies to current problems and real-life business cases, which often revolve around these themes.

Liselotte Siteur, student Econometrics and Data Science
Copyright: UvA / Economie en Bedrijfskunde
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
Frequently asked questions
  • Do you need to excel in mathematics before you start with Econometrics and Data Science?

    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 maths required, please have a look at the entry requirements.

  • Do you need programming skills before you start with Econometrics and Data Science?

    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.

  • The Bachelor's programme is also offered in Dutch. Is there any difference in the English and Dutch taught programmes?

    No, both tracks are identical in terms of level and content. If you choose the English track, you will study alongside Dutch students and students from around the world. All courses will be taught in English. If you find the transition to a fully English-language programme a bit challenging, the Dutch track might be a better fit for you. In the Dutch track, tutorials and some lectures will be conducted in Dutch. You will also complete assignments and exams in Dutch. Each year, the amount of English used in the programme gradually increases, ensuring you a smooth transition to a fully English-taught programme.

    Overview of the Dutch track:

    • Year 1: All lectures, tutorials, assignments and exams are in Dutch.
    • Year 2: Lectures will be in English, tutorials and exams in Dutch.
    • Year 3: All lectures and tutorials are in English. You can write your thesis in Dutch.
       
  • What is the difference between Econometrics and Data Science and Actuarial Science?

    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. The 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.

  • What is the difference between the Bachelors Econometrics and Data Science and Business Analytics?

    The difference is that Business Analytics is data-driven and Econometrics and Data Science are more theory-driven. Econometrics and Data Science students develop econometric models, apply them to micro- and macroeconomic issues and analyse their impact on economic policy. In the Bachelor's degree in Business Analytics, students use data from AI/machine learning techniques to solve complex business-related problems.

  • What is the difference between the Bachelor’s in Econometrics and Data Science and other comparable courses elsewhere?

    Can you switch between the Bachelor's programmes in Actuarial Science and Econometrics and Data Science after the first 2 years?

    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.

  • Can you switch between the Bachelor's programmes in Actuarial Science and Econometrics and Data Science after the first 2 years?

    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.

  • Will you be mentored during your studies?

    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.