MSc Stochastic Modelling & Computational Data Science

Programme Director: Dr Seva Shneer

Programme Code: F7SM-CDS

This programme is available in Edinburgh

This MSc programme is designed in collaboration between both the School of Mathematical and Computer Sciences and the School of Engineering and Physical Sciences. It consists of two coherent and distinctive streams; The first and more theoretical stream will build the student knowledge on the stochastic aspects of data science (Stream SM : Stochastic Modelling and Data Science) The second and more applied stream will build the student knowledge on the computational aspects and engineering applications (Stream CDSE : Computational Data Science and Engineering).

It is important to note that students will only be able to study one of these streams.

Programme Structure

Stochastic Modelling and Data Science Stream

Semester 1 (Mandatory)	Semester 2 (Mandatory)
F21ML Statistical Machine Learning	F71BI Bayesian Inference & Computational Methods
F71MA Statistical Models	F71SP Applied Stochastic Processes
F71PM Advanced Probabilistic Methods	F71SR Research and Industry Topics
Semester 1 (Optional Choose 1 )	Semester 2 (Optional Choose 1)
F71DV Derivatives Markets & Pricing	F71DA Data Analytics and Time Series Analysis
F11AM Mathematical Ecology	F71AE Survival Models
B31XO Sampling and Comp Imaging	F11DA Data Assimilation with Applications to Climate Change Modelling
	F11SS Stochastic Simulation
	B31XN Scalable Inference and Deep Learning

Semester 3:

F71DD MSc Dissertation

Computational Data Science and Engineering Stream

Semester 1 (Mandatory)	Semester 2 (Mandatory)
F21ML Statistical Machine Learning	F71BI Bayesian Inference & Computational Methods
F71MA Statistical Models	B31XN Scalable Inference and Deep Learning
B31XM Information Theory and Communications	B31XP MultiDisciplinary Group Project
B31XO Sampling and Comp Imaging	B81EZ Critical Analysis and Research Preparation

Semester 3:

B31VZ MSc Project