Module one: Machine Learning for Society and Culture (Basics)



Anna Schjøtt Hansen,

Zarah van Hout,

Content and organization

In two courses that build upon each other, we offer social sciences and humanities students a chance to develop their own data analysis and machine learning skills. Analytics has a strong tradition, very established methods, and a broad range of applications in culture, economy, and society. Social analytics extends general analytics toward the analysis of social (media) relationships. Cultural analytics builds on these existing successful analytical methods and applies its techniques and methods to the study of cultural objects. Students will gain knowledge about the theoretical and practical foundations of an analysis of socio-cultural objects. They will also learn about the limits of the current capacities. The first module of the course provides the basics of interactive Python as well as a first real-life case study at the end. We focus on showing you how to use Python for data exploration and the basics of visualisation. You will master the basics of data analysis in Python including NumPy, SciKit-learn and Matplotlib. Once you finish this short course you can move on to module two (insert link once published).

The course is divided into eight smaller sessions organised under two themes:

Interactive Data Exploration with Python

  • Starting with Python
  • Python Lists
  • Arrays
  • Data Frames

Advanced Interactive Data Exploration with Python

  • Data Frame Indexing
  • Control Structures
  • Real-Life Data
  • Basic Visualisation


MA and Postgraduate

Course Duration

3-5 hours

Course Type

Short Course

Participation terms

Both AIDA and non-AIDA students are encouraged to participate in this short course. To register, please send an email to Anna Schjøtt Hansen ( and she will provide the link to the course.

If you are an AIDA Student* already, please also enrol in the same course in the AIDA system (button at the end of the page), in order for this course to be included on your AIDA Course Attendance Certificate.

*AIDA Students should have been registered in the AIDA system already (they are PhD students or PostDocs that belong only to the AIDA Members list (



Modality (online/in person):

Self-study online course

Host Institution
University of Amsterdam

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