In two courses that build upon each other, we offer 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 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 an introduction to interactive Python as well as a first real-life case study at the end. We focus on using Python for data exploration. 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 unit two, where we will start with machine learning.

Python is one of many that can be used for data exploration, if you are interested in other ways to engage with data, you might want to have a look at OER 2, where they use KNIME Analytics Platform.