CS7IS3 – Information Retrieval and Web Search
(Semester 1, 5 ECTS) Explain the process of content indexing in information retrieval including stop word removal, conflation (stemming, string-comparison), and the language dependency of these methods.
School of Computer Science and Statistics
(Semester 1, 5 ECTS) Explain the process of content indexing in information retrieval including stop word removal, conflation (stemming, string-comparison), and the language dependency of these methods.
(Semester 2, 5 ECTS) Appreciate the scope, applications and limitations of artificial intelligence;
(Semester 2, 5 ECTS) The aim of this module is to provide students with a deep understanding of the theory and techniques behind real time animation.
(Semester 2, 5 ECTS) The aims of this module are to give the student skills to model, analyse and solve optimisation problems that arise in data analytics and modern computing and communication systems.
(Semester 1, 5 ECTS) Understand what machine learning is and how it works.
(Semester 1 & 2, 10 ECTS) Assess the theory of classic architecture principles and apply an appropriate architectural model in a team-based application under development
(Semester 1, 5 ECTS) This course will introduce you to the exciting new field of fuzzy systems and the related topics in machine learning and the so-called deep learning neural nets.