More and more data is becoming available in the area of civil engineering that engineers need to make sense of and integrate in their design work ranging from sensor based measurements of infrastrutcure and buildings, to measurements of the environment (weather, water flows), to openly available geographic data. Lately civil engineers even have started to analyse sentiment data users have left on social media platforms such as Facebook or Twitter about their experience while using civil structures. Data engineering is the art of asking the right questions on any of these given datasets whether small or large. The goal of this module is to provide students the basic skills to answer these questions. The module will teach basic data mining and machine learning techniques, both semantical and numerical. The module will also provide insights in data visualization techniques. Students will apply all methods and techniques on a number of data sets from the civil engineering domain using the statistical data analysis software R.
- data mining patterns and sequences
- semantic text mining
- regression analysis
- Bayesian classification
- decision trees and rule based classificatio
- black-box methods
- neural networks and support vector machines
- data visualization: plotting and 3D
Further information about the module can be found on the dedicated Moses-course-site .