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Computational Social Science
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Study programme

Computational Social Science encompasses three years, six semesters and 180 credits (EC). All learning activities are uniquely organised around projects in a realistic context or provided by a real-world client organisation. This will support you in developing and integrating social sciences and humanities expertise (SSHE), digital expertise (DE), research expertise (RE) ánd changemaking expertise (CME).

  • Year 1

    The first year consists of two semester-long, 20-week courses of 30 EC each. In these courses, you will work in small groups (4-5 students) on one (or two) overarching project challenges. Thematically, semesters 1 and 2 focus on climate change and digital surveillance, semester 3 on health and mobility, and semester 4 on inequality.

    The first year provides you with the foundation for successful learning within a transdisciplinary programme. You will understand the complexity of societal challenges, appreciate that these are open to multiple interpretations, and value these different interpretations. You are also introduced to the basics of data science - including programming skills (Juypter notebook, Python) - and empirical research and the individual level of analysis and intervention.

    See examples of project challenges.

  • Year 2

    In the second year, semesters 3 and 4 consist of semester-long, 20-week courses of 30 EC as well and are thematically focused on health and mobility and inequality respectively. The second year introduces you to the analytical level of social practices and systems as well as inviting you to turn your attention to the structural level of analysis. You will work on group assignments proposed by external partners. You are challenged to think about (systemic) digital interventions that may improve the interaction, coordination or communication between stakeholders in a digital system. Finally, you will become familiar with structural cleavages and inequalities in society. You learn how structural inequalities may translate into ‘biased’ applications of Artificial Intelligence (AI), and you are challenged to propose interventions that result in less biased AI solutions.

  • Year 3

    In the third year, you can opt for a minor or electives from other programmes, take an internship or study abroad in the fifth semester. You will complete your degree programme with a 30 EC capstone (or graduation) project for a real-world client organisation in semester 6.

  • Foundation: Appreciating the complexity of social challenges
  • Building blocks: Experimenting with digital interventions of behavioural change
  • Connections: Linking data for better interventions in health or mobility systems
  • Structures: Applying responsible AI to reduce inequality
  • Minor / Elective
  • Capstone: Making social change with digital innovations

See more information in the online Course Catalogue.

The subject of this programme and the many possibilities you have with it appeals a lot to me. You really get a chance to make a difference.

Additional options

Honours programme

If you are ambitious, you can choose to take part in our Honours programme. You’ll take the Honours programme alongside your regular studies. Completion results in you graduating 'with honours': an internationally recognised qualification. If you are up to it, then it's an opportunity not to be missed.


The UvA has partnerships and exchange agreements with more than 100 other universities. As part of your Bachelor's programme you can do an exchange semester abroad. This can be a valuable learning and cultural experience, and a great addition to your degree programme.

Note: You can only go abroad in your third year (fifth semester).


There are various opportunities during the Bachelor’s programme for you to shape your programme to your liking. You can gain 30 elective study credits with courses that are part of another Bachelor's programme at the UvA, thereby doing an additional specialisation. Or you can choose a minor: a cohesive programme lasting half a year (30 EC) taken outside of your own programme. You can choose a minor in Communication Science or Entrepreneurship, for example.


You can devote your fifth semester to taking an internship at an organisation of your choice. This internship will provide you with the opportunity to gain relevant work experience, and apply your academic knowledge in a professional setting. Moreover, the internship will enable you to develop and apply practical skills while putting to use the knowledge that you have gained during the programme.


Contact hours: On average, students will have 14-18 hours of classes per week

  • Large-scale lectures: 4 hours per week
  • Small-scale tutorials: 6 hours per week
  • Practical sessions/workshops: 8 hours per week
  • Self study: 22 hours per week
  • Total study load: 40 hours per week

Year 1 and 2 have the same structure.

Every Monday morning, you will have a check-in meeting with your tutor in small groups. During these meetings, last week’s progress, this week’s plans and tasks, and students' need for support are discussed.

Every Friday, during the check out, you will present and review the progress your project group made and prepare for the project deadline at the end of the day. This creates a weekly deadline and an opportunity for you to reflect on your activities and participate in peer feedback.

The remainder of the week consists of lectures, workshops/practical sessions and out-of-class study activities where you, collaboratively or individually, will work on your projects, watch online lectures, search for data and information, analyse the data, read literature and prepare for assessments.

Study this programme in Dutch?

Are you a Dutch-speaking student? Then you can also participate in our Dutch Bachelor’s programme in Computational Social Science. The Dutch taught programme is exactly the same as the English taught programme.


The final products of your group projects can range from policy briefs and manifesto’s to websites, experimental designs or prototypes of other digital tools and interventions. Your individual assignments will include e.g. literature reviews, research proposals, case study reports, essays, simulations and information visualisations. Every semester, both group projects and individual assignments will be graded (50%/50%).

Assignments or group projects may relate to topics such as:

  • nudging towards sustainable behaviour in people’s homes through interface design of electric appliances
  • applying big data to counter aggression among adolescents in particular regions of the world
  • researching issues of blockchain technology, such as users becoming both consumer and producer, in the pursuit of transparency and sustainability in logistics
  • gaining insight into the spread of infectious diseases
  • signalling human rights violations by means of information technology
  • investigating societal possibilities of digital forensics
  • mapping social movements in an age of (digital) surveillance
  • empowering displaced people (refugees) with technology-enabled solutions

See more examples of project challenges.

Course materials

Examples are:

Acquisti, A., Brandimarte, L., & Loewenstein, G. (2015). Privacy and human behavior in the age of information. Science, 347(6221), 509-514.

Montano DE & Kasprzyk (2002). The theory of reasoned action and the theory of planned behaviour. In Glanz K, Rimer BK, & Lewis FM, Eds. Health Behaviour and Health Education, 67-98.

Wilke, Claus O. Fundamentals of data visualization: a primer on making informative and compelling figures. O'Reilly Media, 2019. (