A close up of a computer server
A computing cluster at the University
(Image Credit: John Cairns / Oxford University Images)

MSc in Advanced Computer Science

About the course

The MSc in Advanced Computer Science at Oxford has been designed to teach a range of advanced topics to graduates of computer science and other mathematical disciplines.

As in other branches of applied mathematics and engineering, improvements in the practice of computing necessitate a deep and broad engagement with the foundations of computer science.

Recognising this, this full-time, twelve-month MSc has been designed to teach the mathematical principles of specification, design and efficient implementation of computing technologies.

The MSc is designed to combine theory and practice. It teaches the advanced techniques and ideas that are being developed in application domains (such as machine learning, verification and computer security) and the rich and diverse theories that underpin them. These include models of computation and data, and mathematical analysis of programs and algorithms.

The course aims:

  • to provide a challenging and supportive learning environment that encourages high quality students to reach their full potential, personally and academically;
  • to provide the foundation for a professional career in computing-based industries;
  • to enhance the skills of a professional who is already working in one of these industries;
  • to provide a foundation for research into the theory and computing;
  • to present knowledge, experience, reasoning methods and design and implementation techniques which are robust and forward-looking.

The Department of Computer Science is committed to the development and application of effective theory based on realistic practice. The MSc in Advanced Computer Science is heavily informed by the department’s consultation and collaboration with industry, and some of the modules were developed through consultation and collaboration with industry. The department believes that only by the interplay of theory and practice can you be trained properly in such a rapidly advancing subject. Practice alerts us to real contemporary problems - theory is a shield against professional obsolescence.

Entrants to the course will come from either a computer science or mathematical background. You may be a recent graduate in computer science and will supplement your knowledge with the kind of sound mathematical basis which is not always found in undergraduate courses. If you are a graduate in mathematics you will apply your training in the context of a rigorous application of the fundamental techniques of computer science.

You will develop knowledge and understanding of a formal disciplined approach to computer science, a range of relevant concepts, tools and techniques, the principles underpinning these techniques and the ability to apply them in novel situations. On subsequent employment, you will be able to select techniques most appropriate to your working environment, adapt and improve them as necessary, establish appropriate design standards for both hardware and software, train colleagues in the observance of sound practices, and keep abreast of research and development.

Course outline

The academic year is split into three terms of eight weeks but work on the MSc course continues throughout the year and is not restricted just to term time. During the three terms of the course, you will choose from modules on various aspects of computer science. Most modules will last for one term and will be between 16 to 24 lectures. In addition, all modules will have associated classes and some may also have practical sessions (labs) associated with them. 

In the third term (Trinity term) you will undertake a dissertation. Subject to meeting the relevant requirements (which may depend upon your module choices, dissertation subject and other academic factors), you may have the opportunity to transfer to a specialist stream of the course prior to completing your dissertation: either the MSc Advanced Computer Science (Artificial Intelligence) or the MSc Advanced Computer Science (Foundations of Computer Science).

A typical week for a student taking three courses in each of the first two terms may be as follows:

  • Lectures - eight hours
  • Tutorial classes - three hours
  • Practicals - four hours
  • Self-directed study, including preparatory reading, problem sheets, revision of material - 20 hours

Total - 35 hours

The split of work may differ depending on whether a course has practicals associated with it. This should be taken as a guide only.

Examples of modules offered:

  • Advanced Security
  • Computational Biology
  • Computational Learning Theory
  • Foundations of Self-Programming Agents
  • Geometric Deep Learning
  • Graph Representation Learning
  • Probabilistic Model Checking
  • Deep Learning in Healthcare
  • Quantum Software 

The options that are offered may vary from year to year as the course develops, and according to the interests of teaching staff. The above examples illustrate the kinds of topics that have been offered recently.

Attendance

The course is full-time and requires attendance in Oxford. Full-time students are subject to the University's Residence requirements.

Resources to support your study

As a graduate student, you will have access to the University's wide range of world-class resources including libraries, museums, galleries, digital resources and IT services.

The Bodleian Libraries is the largest library system in the UK. It includes the main Bodleian Library and libraries across Oxford, including major research libraries and faculty, department and institute libraries. Together, the Libraries hold more than 13 million printed items, provide access to e-journals, and contain outstanding special collections including rare books and manuscripts, classical papyri, maps, music, art and printed ephemera.

The University's IT Services is available to all students to support with core university IT systems and tools, as well as many other services and facilities. IT Services also offers a range of IT learning courses for students, to support with learning and research.

The Department of Computer Science's teaching network comprises over 80 PCs located in the Department of Computer Science and the Practicals Laboratory of the Thom Building, the main building of the Department of Engineering Science. The machines in the Thom Building are mostly used for undergraduate practical sessions, though you may occasionally have a practical session scheduled here.

Additionally there is a server-based remote access service available, such as personal laptop at home or through networked computers in college computer rooms.

Linux is used throughout the teaching network.

The Department of Computer Science Library contains books, monographic series, journals, technical reports and past theses covering the main research interests of the department. It is principally for use by graduate students and staff. You will also be able to access other relevant libraries elsewhere in the University such as the Radcliffe Science Library, the Whitehead Library (at the Mathematical Institute for numerical analysts and formal mathematicians), and the Engineering Science Library (especially for those interested in robotics and machine vision).

The Department of Computer Science houses lecture theatres and seminar rooms in which most of the University lectures in Computer Science take place.

There are department kitchens on each floor and a central common room where you can meet informally. There is an active social committee organising events for staff, students and families.

Supervision

The allocation of thesis supervision for the course is the responsibility of the Department of Computer Science and it is not always possible to accommodate the preferences of incoming graduate students to work with a particular member of staff. Under some circumstances it may be appropriate for a student's thesis work to be supervised by a faculty member outside the department of Computer Science.

You will be assigned an initial supervisor on arrival in Oxford whose role is to act as an academic advisor during the first two terms of the course. In the third term, a thesis supervisor will be agreed on.

Assessment

For the taught modules, the mode of assessment shall be either written assignment or written examination, dependent on the module you are taking.

A dissertation, completed independently under the guidance of an expert supervisor, on a topic of your choice and approved by the supervisor and MSc Course Director will be submitted by the end of the third term (Trinity Term).

Graduate destinations

Many past students have progressed to PhD-level studies at leading universities; other have pursued careers in industry. 

Changes to this course and your supervision

The University will seek to deliver this course in accordance with the description set out in this course page. However, there may be situations in which it is desirable or necessary for the University to make changes in course provision, either before or after registration. The safety of students, staff and visitors is paramount and major changes to delivery or services may have to be made if a pandemic, epidemic or local health emergency occurs. In addition, in certain circumstances, for example due to visa difficulties or because the health needs of students cannot be met, it may be necessary to make adjustments to course requirements for international study.

Where possible your academic supervisor will not change for the duration of your course. However, it may be necessary to assign a new academic supervisor during the course of study or before registration for reasons which might include illness, sabbatical leave, parental leave or change in employment.

For further information please see our page on changes to courses and the provisions of the student contract regarding changes to courses.

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