Software stack

Make sure you’re familiar with a set of software programs to meet your needs. On Tilburg Science Hub, you can learn about how to configure most of these software programs.

Statistical software

  • by far most students use R for data preparation/cleaning and model estimation. We have collected a few tips on how to learn R here.
  • If your more into data science, Python is probably the way to go.

Managing data-intensive research projects

  • Managing a data-intensive research project can be quite a challenge. That’s why we have created Tilburg Science Hub, which features a boot camp that shows you how to manage such projects efficiently.
  • At the core of our thinking lies the use of automated project pipelines - learn how to create one for your project here.

Code versioning


  • Most students write their theses in Word, but a growing number of students has started to shift to a locally installed Latex distribution, or its (freemium) cloud-based alternative Overleaf. You can start typing directly in one of the Tilburg-branded templates.


  • Database management
    • does your data sit somewhere in a database? Then learning SQL (for structured databases) or NoSQL (for unstructured databases) is recommended.
  • Data collection
    • Should you plan on collecting some data via web scraping and APIs, we recommend you to refresh your Python skills.