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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

Classification scheme for the award of a taught master's degree (four units)
Exam sub-board local rules

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ST422 Time Series (0.5) #  (withdrawn 2024/25)

 

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 graduate summary page for prospective students. Changes to course and programme information for future academic sessions can be found on the graduate summary page for future students.