CSU23021 – Microprocessor Systems
(Semester 2, 5 ECTS) This module provides a holistic overview of how a typical general purpose computing system functions, followed by a deep-dive into the various key architectural features of such systems.
School of Computer Science and Statistics
(Semester 2, 5 ECTS) This module provides a holistic overview of how a typical general purpose computing system functions, followed by a deep-dive into the various key architectural features of such systems.
(Semester 2, 5 ECTS) The first part of this module introduces students to concurrency and concurrent
programming. The second part looks at aspects of the function and implementation of operating systems.
(Semester 2, 5 ECTS) This module introduces students to the discipline of software engineering and
requires them to work in groups to complete a complex software project.
(Semester 1, 5 ECTS) Design substantial logic circuits using register transfer descriptions.
(Full Year, 10 credits) The mathematical objects studied in this module are fundamental not just for theoretical computer science but constitute the building blocks for formalising problems and writing down algorithms to solve those problems. The aim of the module is to provide a lifelong ability to operate with the mathematical objects and to make students comfortable with mathematical proofs.
(Semester 1, 5 ECTS) The topics of this module are: the theory and practice of algorithmic design; evaluation algorithm performance; and standard algorithms and data structures.
(Semester 2, 5 ECTS) This module continues directly from Algorithms and Data Structures I and addresses topics including recursion, divide-and-conquer, graph traversal and dynamic programming.
(Semester 2, 5 credits) This module will develop several important ideas in statistical analysis making use of some of the ideas introduced in STU22004. It acts as a bridge to the sophister years by introducing the fundamental ideas that are used in the more advanced statistics modules that will take place then.
(Semester 1, 5 ECTS) This module covers a range of topics in probability theory at an introductory level, with a view towards applications. Overall the goal of the module is to let the students gain familiarity with both analytical and simulation-based methods to deal with applied problems in probability.
(Semester 1, 5 ECTS) This module focuses on the methods and techniques for efficient management
(modelling, manipulation and retrieval) of data and information. It provides a foundation for later modules in database management and advanced information
management.