Computer Science (MSc) 2027 entry

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 St Andrews. 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

  • Object-Oriented Modelling, Design and Programming: introduces and revises object-oriented modelling, design and implementation up to the level required to complete programming assignments within other MSc modules.

• Optional

  • Complex Systems Modelling and Simulation: This module will introduce complex systems modelling and simulation, providing a broad grounding in a range of techniques and their applications to different classes of problems, with a practical focus on modern network-based models and simulation.
  • Computer Architecture: Studies the design and implementation of programming languages.
  • Computer Security: This module reviews key theoretical and practical aspects of Information Security Management.
  • Concurrency and Multi-Core Architectures: Presents the key concepts of programming multi-core/many-core and other parallel architectures.
  • 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.
  • Discrete Optimisation: This module introduces the theory and practice of discrete optimisation, whose problems are central to many real-world applications, ranging from timetabling to transportation networks.
  • Distributed Systems: Covers the fundamentals of distributed systems, with reference to system models, programming languages, algorithmic techniques, concurrency and correctness.
  • Fundamentals of Software Engineering: covers fundamental theory and practice of Software Engineering.
  • Human Computer Interaction Principles and Methods: This module provides a grounded introduction to the principles of human computer interaction in the context of evaluation paradigms.
  • Information Visualisation: This module provides an introduction to information visualisation. It focuses on the question of how to utilise visual representations to make information accessible for exploration and analysis.
  • Interactive Software and Hardware: This module develops prototype-building skills for a wide range of interactive technologies.
  • 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.
  • 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).
  • Software Architecture and Design: introduces students to the concepts of software architecture and design as aids to developing good quality software.
  • 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.
  • Video Games: Builds on general-purpose programming abilities acquired earlier to develop games programming skills through lectures and laboratories, culminating in the creation of actual games.
  • 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
  • Databases
  • Distributed Systems
  • Logic and Software Verification
  • Programming Language Design and Implementation
  • Signal Processing: Sound, Image, Video
  • Video Games

• Dissertation

  During the second semester, students work with staff to define and agree a topic for the extended project. They will work on it during the final three months of the course, finishing with 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.