MSc in Data Science

Page contents > Paper 5 options list | Prerequisite Requirements and Mutually Exclusive Options

Programme Code: TMDS

Department: Statistics

For students starting this programme of study in 2020/21

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 four compulsory courses, options to the value of one unit and a dissertation 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	MY470 Computer Programming (0.5)
	OR
	Students who can demonstrate equivalent prior knowledge of MY470, via transcripts of prior qualifications, may instead take a further 0.5 unit course from Paper 5:
	Paper 5 options list
Paper 2	ST445 Managing and Visualising Data (0.5) ^#
Paper 3	ST447 Data Analysis and Statistical Methods (0.5) ^#
Paper 4	ST443 Machine Learning and Data Mining (0.5) ^#
Paper 5	Courses to the value of 1.0 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)
	ST449 Artificial Intelligence (0.5)
	ST451 Bayesian Machine Learning (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) ^#
Paper 6	ST498 Capstone Project (1.0) ^#

Paper 5 options list

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)
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) ^#
ST449 Artificial Intelligence (0.5)
ST451 Bayesian Machine Learning (0.5) ^#

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.