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MSc in Data Science

Programme Code: TMDS

Department: Statistics

For students starting this programme of study in 2023/24

Guidelines for interpreting programme regulations


Full-year programme. Students must take three compulsory courses, options to the value of 1.5 unit(s) and a Capstone Project as shown.

Please note that places are limited on some optional courses. Admission onto any particular course is not guaranteed and may be subject to timetabling constraints and/or students meeting specific prerequisite requirements.

Paper

Course number, title (unit value)

Paper 1

ST445 Managing and Visualising Data (0.5) #

Paper 2

ST447 Data Analysis and Statistical Methods (0.5) #

Paper 3

ST443 Machine Learning and Data Mining (0.5) #

Paper 4

Courses to the value of 1.5 unit(s), including at least 0.5 unit(s) of ST courses from the following:

 

MA407 Algorithms and Computation (0.5) #

 

MA424 Modelling in Operations Research (0.5) #

 

MY459 Quantitative Text Analysis (0.5) #

 

MY461 Social Network Analysis (0.5)

 

MY470 Computer Programming (0.5)

 

ST405 Multivariate Methods (0.5) #

 

ST411 Generalised Linear Modelling and Survival Analysis (0.5) #

 

ST422 Time Series (0.5) #

 

ST429 Statistical Methods for Risk Management (0.5) #

 

ST436 Financial Statistics (0.5) #

 

ST444 Computational Data Science (0.5) #

 

ST446 Distributed Computing for Big Data (0.5) #

 

ST449 Artificial Intelligence (0.5)

 

ST451 Bayesian Machine Learning (0.5) #

 

ST454 Bayesian Data Analysis (0.5) #

 

ST455 Reinforcement Learning (0.5) #

 

ST456 Deep Learning (0.5) #

 

ST457 Graph Data Analytics and Representation Learning (0.5) #

Paper 5

ST498 Capstone Project (1.0) #

Prerequisite Requirements and Mutually Exclusive Options

# means there may be prerequisites for this course. Please view the course guide for more information.

Note for prospective students:
For changes to graduate course and programme information for the next academic session, please see the . Changes to course and programme information for future academic sessions can be found on the .