Data from automated processes is often complex and high-dimensional. In this course, we teach you modern methods of multivariate data analysis and how to apply them to real process data. You work through the full workflow of an analysis project: you examine the structure of your data, prepare it, choose suitable statistical methods, and interpret your results for a given problem. Along the way, you learn to handle common challenges such as collinearity and to use techniques such as data compression, alignment, and projection methods.

Much of the course is hands-on — in group work on real-world problems and with professional software, you build the skills to plan and carry out your own analyses and to communicate your findings.