58³Ô¹Ï

Course information may change. Module information and course content, teaching and assessment may change each year and after you have accepted your offer to study at the University of 58³Ô¹Ï. We display the most up-to-date information possible, but this could be from a previous academic year. For the latest module information, see the module catalogue.

• Compulsory

• Optional

  • Critical Systems Engineering: The aim of this module is to provide students with an understanding of the concepts and development techniques used for critical, socio-technical systems.
  • Data Ethics and Privacy: The aims of this module are to introduce students to the various ethical dilemmas that are arising in our 'data-driven society'.
  • Data-Intensive Systems: CS5052 is an advanced research-focused module, which presents the programming paradigms, algorithmic techniques, and design principles for large-scale distributed systems
  • Databases: Introduces data models, modeling techniques, relational design and a range of issues in database implementation.
  • Dissertation in Computer Science: This module is an individually supervised MSc project on a topic suitable to the student's programme in the School of Computer Science.
  • Fundamentals of Software Engineering: covers fundamental theory and practice of Software Engineering.
  • Group Project and Dissertation in Computer Science: This module is a group-based MSc project on a topic suitable to the students' programmes in the School of Computer Science.
  • Language and Computation: This module covers the major aspects of natural language processing and speech understanding.
  • Logic and Software Verification: This module motivates the need for formal methods and software verification approaches as model checking for guaranteeing the correctness of software systems.
  • Machine Learning: This module covers the essential theory and algorithms of Machine Learning, including mathematical foundations and methodological approaches.
  • Machine Learning for Data Analysis: This module covers many of the methods found under the banner of Datamining, building from a theoretical perspective but ultimately teaching practical application.
  • Masters Programming Projects: This module reinforces key programming skills gained in CS5002, by means of a series of coursework assignments posed as small programming projects.
  • Principles of Computer Communication Systems: This module aims to equip students with a deep knowledge of fundamental concepts and terminologies of computer communication systems (CCS).
  • Programming Principles and Practice: This module introduces computational thinking and problem solving skills to students who have no or little previous programming experience.
  • Software Architecture and Design: introduces students to the concepts of software architecture and design as aids to developing good quality software.
  • Software Product and Project Management: introduces principles, processes and tools for managing large, realistic software projects and products.
  • Software Quality: covers essential tools and skills for ensuring and maintaining software quality.
  • Symbolic Artificial Intelligence: The module gives an overview of traditional AI methods and the philosophy of AI.
  • Uncertainty in Artificial Intelligence: This module covers reasoning and decision making in the presence of uncertainty.
  • Web Technologies: This module covers the foundations of modern, dynamic Internet applications. It teaches foundational World Wide Web technologies as well as back-end and Web APIs.

• Additional optional

  Students may take up to two of the following:

  • Advanced Communication Networks and Systems
  • Computer Architecture
  • Computer Graphics
  • Computer Security
  • Concurrency and Multi-Core Architectures
  • Constraint Programming
  • Databases
  • Distributed Systems
  • Logic and Software Verification
  • Programming Language Design and Implementation
  • Signal Processing: Sound, Image, Video
  • Video Games 

• Dissertation project

  During the second semester, students work with staff to define and agree upon a topic for the extended project, which they will work on during the final three months of the course. The project finishes in a 15,000-word dissertation. Dissertation projects may be group-based or completed individually, though students are assessed individually in either case. 

  The dissertation typically comprises: 

  • a review of related work
  • the extension of existing or the development of new ideas
  • software implementation and testing
  • analysis and evaluation

  Each project is supervised by one or two members of staff, typically through regular meetings and reviews of software and dissertation drafts.