School of Computer Science and Statistics
(Semester 2, 5 ECTS) This module introduces the research process. Starting with the formulation of a
research question, it covers completing a literature review, choosing an appropriate
research design, data collection, data analysis and how to communicate research
findings.
(Semester 1, 5 ECTS) Classical multivariate techniques of principal component analysis, clustering, discriminant analysis, k-nearest neighbours, and logistic regression are investigated.
(Semester 1, 5 ECTS) Introduction to Forecasting; ARIMA models, data transformations, seasonality, exponential smoothing and Holt Winters algorithms, performance measures. Use of transformations and differences.
(Semester 1 & 2, 10 ECTS) This is a problem based learning module. It requires students to apply what they have learned in other modules in MSISS in a simulated real life problem.
(Semester 2, 5 ECTS) The aim of the module is to introduce students to the crucial role that Information Systems play in all aspects of society and the workplace as these domains undergo trans-formative change.
(Semester 1, 5 ECTS) This module aims to provide an opportunity for students to develop their hands on
skills in data analysis.
(Semester 2, 5 ECTS) Information modelling and databases.