Model-based Machine Learning leverages the powerful framework of Probabilistic Graphical Models (PGMs) and recent developments in probabilistic programming to allow the combination of domain knowledge with data driven methods in a very simple way.

Business Analytics (BA) is about exploring and analysing large amounts of data to gain insight into past business performance in order to guide future business planning. The methods will be applied to various business cases with aim to demonstrate how to extract business value from data, provide data-driven decision support along with effective data management principles. In this course, advanced machine learning techniques are used so understanding of data science and machine learning basics is required as well as a good level of programming skills is expected.

Understanding how a transport system operates is at the core of this course. Students will gain knowledge on the key mathematical methods used in the representation of people’s and vehicle’s movement, the network and service performance and key strategies for control and improved efficiency of mobility systems. This course combines key methodological knowledge gains with examples applications from different dimensions of the mobility paradigm.