Data Science for Decision Making will familiarise you with methods, techniques and algorithms that can be used to address major issues in mathematical modelling and decision making. You will also get hands-on experience in applying this knowledge through computer classes, group research projects and the thesis research. The unique blend of courses will equip you with all the knowledge and skills you’ll need to have a successful career.
Widespread applications
Data Science for Decision Making links data science with making informed decisions. It has widespread applications in business and engineering, such as scheduling customer service agents, optimising supply chains, discovering patterns in time series and data, controlling dynamical systems, modelling biological processes, finding optimal strategies in negotiation and extracting meaningful components from brain signals. This means you'll be able to pursue a career in many different industries after you graduate.
Programme topics
Data Science for Decision Making covers the following topics:
* production planning, scheduling and supply chain optimisation
* modelling and decision making under randomness, for instance in queuing theory and simulation
* signal and image processing with emphasis on wavelet analysis and applications in biology
* algorithms for big data
* estimation and identification of mathematical models, and fitting models to data
* dynamic game theory, non-cooperative games and strategic decision making with applications in evolutionary game theory and biology
* feedback control design and optimal control, for stabilisation and for tracking a desired behaviour
* symbolic computation and exact numerical computation, with attention to speed, efficiency and memory usage
* optimisation of continuous functions and of problems of a combinatorial nature
