Management Science and Information Systems Studies
Year 4
The fourth year (Senior Sophister year) of the MSISS programme is centred around the project which forms a considerable part of the work for the year. These projects are carried out for real world clients.
Compulsory Modules
Students take the following compulsory modules from the School of Computer Science and Statistics:
STU44003 – Data Analytics
(Semester 1 & 2, 10 ECTS) The aim of the course is to introduce the students to a set of techniques including classification and regression trees, and ensemble methods.
STU44091 – MSISS Final Year Project
(Semester 1 & 2, 20 ECTS) The aims of the project are to integrate the theoretical and practical knowledge of the student across all of the years of their study and to provide a practical demonstration of their capability in executing a challenging and large-scale research project.
STU45006 – Strategic Information Systems
(Semester 1 & 2, 10 ECTS) The objective of this course is to introduce students to Strategic Information Systems in the workplace and society.
Optional Modules
Optional modules offered by the School of Computer Science and Statistics
Students in Year 4 choose 20 credits of optional modules from the following lists of modules offered by the School of Computer Science and Statistics and other schools.
CSU44051 – Human Factors
(Semester 1, 5 ECTS) The module provides an introduction to the field of Human-Computer Interaction, focused both on understanding human interactions with technology and on the design of useful and usable interactive systems.
CSU44081 – Entrepreneurship & High-Tech Venture Creation
(Semester 2, 5 ECTS) Explain how high tech venture creation operates, with an emphasis on the processes developed by the Silicon Valley venture community over the past 20 years
STU34501 – Applied Linear Statistical Methods I
Offered in 2023/24 Module CodeSTU34501Module Name Applied Linear Statistical Methods IECTS Weighting [1]5 ECTS Semester taughtSemester 1Module Coordinator/s Dr. Jason Wyse Module Learning Outcomes On successful completion of this module,…
STU34502 – Applied Linear Statistical Methods II
Not running 2022/23. Module Code STU34502 Module Name Applied Linear Statistical Methods II ECTS Weighting [1] 5 ECTS Semester taught Semester 2 Module Coordinator/s Alessio Benavoli Module Learning Outcomes On…
STU34507 – Statistical Inference I
(Semester 1, 5 credits) This module introduces different statistical modelling used for analysing stochastic processes defined in the spatial and/or time domains. These have many applications (e.g. engineering, finance, genetics).
STU34508 – Statistical Inference II
(Semester 2, 5 ECTS) Specific topics addressed in this module include:
examples of stochastic processes, the Markov property and discrete state space Markov chains, Chapman-Kolmogorov equation, convergence to stable distribution, Poisson processes and their properties and applications, further discrete state space Markov processes,
Brownian motion and geometric Brownian motion.
STU44005 – Decision Analysis
(Semester 1, 5 credits) An introduction to the field of Operations Research.
Optional modules offered by other schools
BUU44531 Financial Reporting and Analysis I (5 ECTS )
BUU44532 Financial Reporting and Analysis II (5 ECTS)
BUU44706 Natural Capital Accounting (5 ECTS )
BUU44700 Sustainable Finance (5 ECTS )