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In the Bachelor’s in Business Analytics, you learn how to apply techniques from AI and machine learning, econometrics and statistics, optimisation, computer science and programming within a data-rich business and management environment. These methods will help you to understand and use data to solve a wide array of business cases and problems within organisations. How can we predict and manage what product, when or at what price level our customers will buy next time? How can we work with large language models? How can we detect and prevent fraud in our online business? How do social media popularity and content affect a brand’s success on different platforms? What can we do by using big data to make our manufacturing process more efficient? As a business analyst, you help organisations improve their performance with your analysis, interpretation and recommendations on these kinds of questions, using data.

The programme

Our Bachelor’s programme in Business Analytics integrates 3 important fields: analytics, business and computer science (machine learning, artificial intelligence). This combination makes your degree stand out to future employers.  

Although the focus differs significantly from that of our Bachelor’s in Econometrics and Data Science, you will share lectures and study groups in some parts of the programme. 

  • Your study week

    All courses are taught in English and combine theory and practice. You will work on business cases and learn how to carry out data science and business analytics projects from beginning to end.

    • Lectures (8 hours): Lectures give an introductory overview of the course content. You will attend them together with your fellow students. You take notes and have the opportunity to ask questions.
    • Seminars (6 hours): During seminars, you will discuss specific subjects from the lectures in small groups. Exercises and practice assignments will help you to become adept with the theory.
    • Practicals (2 hours): During practicals, you learn how to work with various mathematical and statistical computer programs.
    • Self-study (24 hours):  During your study week, you spend time studying theory and preparing for lectures, seminars, exams or presentations. 
    • Skills & Connect: In the first 6 months of your studies, you will receive weekly coaching from a senior student in a fixed 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.
    • Exams: At the University of Amsterdam, the academic year is divided into 2 semesters and 6 study blocks. In each block, you take courses that are assessed through exams. Almost all courses have a final exam at the end, and some also have a midterm exam halfway through. The exams are usually written and last 2 to 3 hours. You are generally allowed to use a calculator, and in some cases a formula sheet. You solve quantitative exercises with pen and paper and explain your reasoning. You receive partial credit for partially correct answers. If you fail an exam, you will have a chance to take a resit after a few weeks. 
  • Year 1: develop a solid foundation

    You will gain a basic understanding of how organisations work and interact with their environment. At the same time, you learn how to apply quantitative methods and techniques to analyse these processes and activities. You will follow several foundational courses in mathematics and statistics, such as Calculus, Linear Algebra, Probability Theory and Statistics. In addition, you take introductory courses in Artificial Intelligence, Programming and Data Science, which help you apply mathematical methods to real-world problems. Together, these courses form a solid foundation for the more advanced and specialised subjects in the following years.

    Binding Study Advice (BSA)

    All Bachelor’s programmes at the University of Amsterdam are subject to a Binding Study Advice (BSA). For this programme, you need to earn at least 48 of the 60 ECTS credits in your 1st year. If you do, you will receive a positive study advice and can continue into the 2nd year. 

  • Year 2: specialise in business analytics and develop entrepreneurial skills

    In the 2nd year, you further develop your ability to analyse and model business problems in different domains, using analytical methods from data science, AI and machine learning, and computer science. You will take courses in optimisation, machine learning, algorithms and data structures, and a hackathon.   

  • Year 3: customise your programme

    Semester 1

    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, taking a minor or 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 your knowledge and stand out from the crowd with a mini study programme in a completely different field, such as Philosophy, Law or Italian Studies.  At the UvA, you can choose from a wide range of Dutch- and English-taught minors. 
    • Choose 5 electives from a list of Bachelor’s courses.

    Semester 2

    In the 2nd semester, you take common courses that strengthen your background in business analytics:

    • Text Retrieval and Mining (6 ECTS)
    • Marketing Analytics (6 ECTS)
    • Computer Systems and Engineering / Information and Data Management (6 ECTS)
    • Bachelor Thesis and Thesis Seminar Business Analytics (12 ECTS)
  • Thesis

    Is there a particular recent development that sparks your enthusiasm, or do you have a great business idea of your own? While writing your thesis, you have the chance to explore it fully while training your ability to conduct relevant research independently. Your thesis is the final requirement for your graduation. Supervised by our researchers, you will follow a clearly defined path that will lead to your graduation with a Bachelor's degree. 

    Data challenge - BSc Business Analytics
    Data challenge

    At the end of the Bachelor's Business Analytics, students work on an empirical or theoretical business analytics project. This can be an academic or a company project.

    Watch our students' experience on this final assignment.

  • Watch the recording of the online information session
    Watch the recording of the online information session

    The programme director of the Bachelor’s programme in Business Analytics, explains during this online information session what you can expect of this challenging Bachelor's programme. Additionally, two of our students share their experiences with this Bachelor’s and student life in Amsterdam.

The courses in your Bachelor's

COURSES SEM 1 SEM 2 SEMESTER 1 SEMESTER 2 EC
  • Analytics for a Better World
    Period 1
    6

    This hands-on course revolves around real-life data-centric cases with a societal impact. It teaches you some basic business analytics methods and simple machine learning techniques so that you get a solid, practical introduction to the world of analytics. You analyse, interpret and process the data yourself.

  • Mathematics 1: Calculus
    Period 1
    6

    This course focuses on calculus at the academic level. The lectures give you a general introduction to the theory. During tutorials, you deepen theoretical insights through discussion of practical problems, exercises and further applications.

  • Probability Theory and Statistics 1
    Period 2
    6

    This course gives you a solid understanding of probability theory and statistics; an indispensable basis for many subsequent courses in the programme. During lectures, we discuss relevant topics step by step. The exercises you prepare for the tutorials serve as an illustration of their application.

  • Programming with Computational Thinking
    Period 2
    6
  • Data Visualisation and Storytelling
    Period 3
    6

    This course introduces the principles of transforming data into clear and compelling visual insights. You learn how to move beyond default charts and communicate data-driven messages effectively. The course combines basic technical skills with narrative thinking. You learn how to select appropriate visualisations, apply design principles based on human perception, and structure a clear story around data, from question to insight to recommendation.

  • Finance for Quantitative Economics
    Period 4
    6

    This course is your introduction to modern finance in today’s business landscape. 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 gives you a solid basis in linear algebra, which you need for the rest of your studies in Business Analytics and its different applications. You practise the theory through exercises and will also learn how to use computer software (R) to solve larger problems.

  • AI, Privacy and Global Cybersecurity for Business Analytics
    Period 5
    6

    In this course, you learn how to identify common risks in fields such as AI, data protection and cybersecurity, how to mitigate those risks and how to document them.

  • Probability Theory and Statistics 2
    Period 5
    6

    In this course, you focus further on probability theory and statistics and build on what you learned in PBS 1. We help you create a sound theoretical basis step by step. Each step comes with exercises that we discuss during weekly tutorials. Writing code in a software package (e.g. R) for simple simulations is also part of this course.

  • Introduction Data Science
    Period 6
    6

    This course covers the basics of how and when to perform data preprocessing. This essential step in any data analysis and machine learning project is when you get your data ready for modelling. You also prepare and give a presentation on a related scientific subject.

COURSES SEM 1 SEM 2 SEMESTER 1 SEMESTER 2 EC
  • Algorithms and Data Structures in Python
    Period 1
    6

    This course gives you fundamental knowledge and understanding of data structures and algorithms. Learn about common algorithms, algorithmic paradigms and data structures used to solve these problems. Use the Python programming language to implement and test algorithms and data structures on realistic datasets.

  • Mathematics 3: Advanced Linear Algebra
    Period 1
    6

    In this course you learn about different methods and results from linear algebra and real analysis. You also use Python to apply these methods to problems and report on the results.

  • Machine Learning
    Period 2
    6

    This course provides an introduction to machine learning methods and models for students with little or no knowledge of the subject. Learn about main characteristics, apply methods on different types of data and assess the performance of methods using different metrics.

  • Operations Research - Deterministic Methods
    Period 2
    6

    This course introduces various modelling and solution methods in operations research when the parameters of optimisation problems are deterministic. In addition to investigating the mathematical principles and the algorithms, you also model and solve problems yourself.

  • International Management Consulting - Operation Excellence
    Period 3
    6

    Managing a business involves identifying, analysing and improving organisational processes. In this course, you learn about Lean Six Sigma’s DMAIC (Define, Measure, Analyse, Improve, Control) model, the world standard for problem- analysis in business and industry.

  • Econometrics 1
    Period 4
    6

    Econometrics uses economic theory, mathematics, and statistics to quantify, model, analyse and understand economic phenomena. In this course, you explore and learn how to apply the multiple regression model. This course is an implicit entry requirement of the second-year course Empirical Project.

  • HR Analytics
    Period 4
    6

    With HR analytics, you can assess the impact of HR initiatives on employees, teams, the organisation and, consequently, on business results. This course gives you the theoretical background on strategic human resource management (HRM) and HR analytics and their application in organisations.

  • Accounting and Control
    Period 5
    6

    In this course you focus on developing tools and frameworks for analysing the financial position and performance in external markets of individual organisations and their subunits (including business units, products and customers).

  • Operations Research - Stochastic Methods
    Period 5
    6

    This course gives you an introduction to the theories behind operations research when the application of deterministic models falls short, for example when randomness and uncertainty play a significant role.

  • Entrepreneurship - Hackathon
    Period 6
    6

    This immersive course consists of a mix of entrepreneurship lectures and workshops and a hands-on hackathon in which your student team develops a prototype of a novel digital product based on a solid business model.

COURSES SEM 1 SEM 2 SEMESTER 1 SEMESTER 2 EC
  • Free-choice electives: studying abroad, minor or electives
    Period 1
    Period 2
    Period 3
    30

    Minor programme, studying abroad, company internship or 5 elective courses.

  • Language Technologies and Models
    Period 4
    6

    In this course, you explore ways of processing documents in natural human language. This includes efficient search, knowledge mining, conversational bots, document classification, automated translation and automated summarisation.

  • Marketing Analytics
    Period 4
    6

    In this course you focus on methods and models to analyse, predict and manage marketing performance to optimise campaigns and strategies. By understanding which marketing instruments and activities are most effective, companies can allocate their resources more efficiently and make better, data-centric strategic decisions.

  • Computer Systems and Engineering - Information and Data management
    Period 5
    6

    Blockchain, big data analytics and artificial intelligence are changing how we work, communicate, compete, socialise and much more. This course provides you with a deeper understanding of some of the most important digital technologies and their underlying principles.

  • Bachelor’s Thesis and Thesis Seminar Business Analytics
    Period 5
    Period 6
    12

    This is the skills part of the Bachelor’s Thesis Seminar, which you take in parallel with Bachelor's Thesis Seminar Business Analytics - Research Project. This course gives you the skills to conduct a business analytics project (a design science research project) and to write a Bachelor’s thesis reporting on it. Is there a recent development or business idea that sparks your enthusiasm? While writing your thesis, you have the chance to explore it while training your ability to conduct relevant research independently.

Compulsory course
Elective

The courses and course content are based on the current academic year, 2026–2027, and may change for the following academic year.

Do you want to know more about the courses?

he course catalogue provides detailed information for each course, including its content, assessment methods and literature.

Hi, I'm Mariam! I'm a Bachelor’s student in Business Analytics from Georgia. Got questions about studying at the UvA? Get in touch. Chat with Mariam
Additional options during your studies
Siri
Real-life case: human abilities of GPT (or Siri) 

Have you ever wondered how GPT, Claude, Siri or Google Maps can understand, interpret, and respond to your questions simply by hearing your voice? The technology behind this is called natural language processing (NLP) and large language models (LLMs). NLP and LLMs focus on giving computers human abilities in relation to language, such as the ability to understand spoken words and text. During this Bachelor’s you learn about the wide range of NLP applications: from chatbots and email filters to translation, voice translation and a simple spell check. 

Deepfakes
Real-life case: use of generative AI and consequences 

The rise of deepfakes presents a significant challenge. Deepfakes are manipulated or synthesised videos, photos, or audio recordings that appear real. AI technology can replace faces, manipulate facial expressions, and even synthesise speech. This makes it increasingly difficult to distinguish between real and fake content. This poses serious risks, including spreading misinformation, deception, and potential harm to individuals or organisations. How can we recognise, manage and prevent such risks? During this Bachelor’s, we continuously pay attention to the ethical issues that arise when collecting, analysing and using data. 

Mahika Raj
The programme actively discusses societal and environmental issues and how our study can be effectively used in coming up with solutions. The lecturers also share their experiences which give a good view of real life applications of our study. Mahika Raj, student Business Analytics

Sustainability, responsibility and ethics integrated in the curriculum

In this Bachelor’s programme, you learn about business, big data, AI and machine learning and computer science, and also about social issues such as the environment, sustainability, climate and famine. You learn how ethical, social and sustainability issues factor into business decisions and can be integrated into a business strategy.  

How are these themes integrated into the curriculum?

For example, the course Analytics for a Better World revolves around real-life cases with a high societal impact. Ethics is also a key and recurring topic in the study programme: what are and aren’t you allowed to do with data?   In the course AI, Privacy and Cybersecurity for Business Analytics, along with main concepts and topics in business law, you also focus on topics such as data protection, privacy and data in the digital world and ethics in the context of data -centric business. 

Throughout this 3-year Bachelor’s programme, ethics, (corporate social) responsibility and sustainability are recurring topics. 

Data challenge - BSc Business Analytics
Data challenge

At the end of the Bachelor's Business Analytics, students work on an empirical or theoretical business analytics project. This can be an academic or a company project.

Watch our students' experience on this final assignment.

Frequently asked questions
  • What's the difference between the Bachelor's in Business Analytics and Econometrics and Data Science?

    The difference between the Bachelor’s programmes in Business Analytics and in Econometrics and Data Science is that Business Analytics is data-driven and Econometrics and Data Science is theory-driven.

    •  Business Analytics students use data and apply AI and machine learning technologies to address complex business-related issues across a broad range of fields: finance, marketing, accounting, human resources, entrepreneurship and other subdomains in business. Business Analytics bridges the gap between analytics and computer science on the one hand and economics (including business economics) on the other. 
    • Econometrics and Data Science students develop econometric models, apply them to micro- and macroeconomic issues and analyse the impact of these on economic policy.

    The level of mathematics and statistics in Business Analytics is similar to that in the Econometrics and Data Science programme. The main difference lies in the balance between the practical and theoretical aspects of mathematical topics and methods. Business Analytics students focus more on the applied and practical side of mathematics in follow-up courses. The mathematics in Business Analytics is just as challenging as in the Bachelor’s in Econometrics and Data Science.

  • Do you need to excel in mathematics before you start with Business Analytics?

    It is important that you both enjoy and are good at mathematics in the Business Analytics programme. In the 1st year in particular, foundational courses in mathematics and statistics feature heavily. The level of mathematics in Business Analytics is similar to that in the Bachelor’s in Econometrics and Data Science. The main difference is the balance between the applied use and the theory of mathematical topics and methods. After similar mathematics courses, Business Analytics students focus more on the applied and practical side of mathematics in the follow -up courses. The mathematics in Business Analytics is just as challenging as in Econometrics and Data Science. 

  • Do you need programming skills before you start with Business Analytics?

    No. You learn everything you need to know about programming during the programme.

  • What kind of courses will you take?

    The Bachelor’s programme in Business Analytics focuses on 3 main areas of study: analytics, business and computer science. You will take courses in programming, artificial intelligence, mathematics, statistics and econometrics. You will also take courses in finance, marketing, entrepreneurship, accounting, organisational studies and strategy. All courses have a practical component, so you can apply what you have learned straight away.

  • Why is this a unique Bachelor's programme?

    This Bachelor’s programme prepares you comprehensively for the future. After obtaining your Bachelor’s degree, for example, you will be able to build a self-driving vehicle or calculate the best price for a plane ticket or hotel room. During our 3-year Bachelor’s programme, you will learn everything there is to know in the fields of mathematics, statistics, business administration and artificial intelligence; knowledge and skills you need, to tackle the challenges described above. There are just a few Bachelor’s programmes in the Netherlands that offer this combination of knowledge and skills.

  • 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 you will have 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.  

    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.