External summary

In the study of physical systems, mathematical models are frequently used to explain and predict their behaviour. Even when these models are simple, their solutions are generally not. Usually, there is no analytical solution in terms of explicit mathematical formulas. In such circumstances one has to resort to numerical solution or computer simulation. The resulting calculations are some of the most computationally demanding ever conceived, running for days on powerful computers. The importance of efficient algorithms (i.e. recipes for computation) in these applications is clear. In the other direction, the physical basis for computation is under study by theoretical computer scientists, with "quantum computers" generating much interest of late.

Educational aims of programme

This joint programme addresses these issues by drawing on Edinburgh's strengths in computational physics and the design and analysis of algorithms to enable students to develop a strong interdisciplinary background covering relevant topics in both Computer Science and Physics.

In Computer Science students undertake a wide variety of practical exercises and projects which reinforce and build on lecture material. The Computer Science material all falls within the scope of the QAA Computing Benchmark. Communication skills, initiative, professionalism and the ability to work with others are developed as integral parts of the learning process. In their final year students undertake a major individual practical project which is normally interdisciplinary between the two subjects.

Programme outcomes: Knowledge and understanding

• have a knowledge and understanding of the principles of operation of computers from application programs down through system software to hardware
• have a knowledge and understanding of the principles of operation of computer networks
• understand the concept of abstraction and its importance in the design of computer based systems
• understand the software development process
• understand the underlying mathematical concepts which allow computer scientists to reason about computers and computer based systems
• have an awareness of the social, professional, ethical and legal issues involved in the use of computing system

Programme outcomes: Graduate attributes - Skills and abilities in research and enquiry

The ability to:

• deploy analytical and problem solving skills and to synthesise solutions

Programme outcomes: Graduate attributes - Skills and abilities in personal and intellectual autonomy

The ability to:

• specify and design computer based systems
• apply formal design procedures to the design of computer based systems
• derive an abstract representation of a problem from from its detailed description

Programme outcomes: Graduate attributes - Skills and abilities in communication

The ability to:

• work effectively as part of a development team
• communicate effectively through a variety of media including oral, visual, written, diagrammatic and on-line

Programme outcomes: Graduate attributes - Skills and abilities in personal effectiveness

The ability to:

• make effective use of learning materials and to acquire and apply knowledge from a variety of sources
• deploy logical, analytical, and problem solving skills and to synthesise solutions
• show self-direction and time management skills when working independently

Programme outcomes: Technical/practical skills

The ability to:

• develop and implement computer based systems
• select an appropriate algorithm for the solution of a given problem
• use appropriate support tools during the development process
• operate computing equipment and software systems effectively

Programme structure and features

For formal definitions, including details of compulsory and optional course choices, consult the Degree Programme Table. Look at the list of Informatics courses to discover what courses belong to which subject area.

Teaching and learning methods and strategies

Teaching contact through lectures, scheduled tutorials and laboratory sessions is supplemented with additional supervised drop-in laboratory time for several courses.  Formative exercises are often included in the delivery of a course to direct learning to meet learning outcomes. INFBase provides learning support for Informatics students where they can access course tutors out with scheduled tutorial times.

Assessment methods and strategies

Methods of assessment of intended learning outcomes include written examinations, online programming examinations and summative course work assignments.  Students complete individual and group projects as part of their degree programme, culminating in the honours project in the final year.

The final honours degree classification of the programme is based equally on performance in third and fourth years. Degrees are classified according to the University's standard marking scale with boundaries at 70%, 60%, 50% and 40%. Students can be awarded an ordinary degree on the basis of their third year marks.

Career opportunities

Computers are now ubiquitous in modern life. The most interesting opportunities in the future are open to those who really know about computing, software and information systems.  Our graduates can choose from a wide range of opportunities in industry, commerce, government and academia; the majority of Informatics graduates enter employment relating to their degree, while others decide to continue within academia to pursue their research interests.

Other items