THE UNIVERSITY of EDINBURGH
DEGREE REGULATIONS & PROGRAMMES OF STUDY 2019/2020

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Degree Programme Specification
BSc (Honours) Artificial Intelligence & Computer Science
 

BSc (Honours) Artificial Intelligence & Computer Science

To give you an idea of what to expect from this programme, we publish the latest available information. This information is created when new programmes are established and is only updated periodically as programmes are formally reviewed. It is therefore only accurate on the date of last revision.
Awarding institution: The University of Edinburgh
Teaching institution: The University of Edinburgh
Programme accredited by:

see accreditation pages

Final award: BSc Honours
Programme title: BSc (Honours) Artificial Intelligence & Computer Science
UCAS code: GG47
Relevant QAA subject benchmarking group(s): Computing
Postholder with overall responsibility for QA: John Longley
Date of production/revision: April 2012

External summary

Artificial Intelligence studies the principles and mechanisms underlying intelligent processes in humans and other living organisms and attempts to apply such knowledge to the design of computer-based systems and to the understanding of natural intelligence. Computer Science, for its part, studies the understanding, design, implementation and the use of computing systems.

The mixtures of complementary and overlapping aspects make Artificial Intelligence and Computer Science a good degree combination.

Educational aims of programme

  • develop graduates possessing a thorough understanding of the theoretical and practical aspects of Artificial Intelligence and Computer Science and of their interrelationships (AI & CS)
  • equip students with advanced scientific and engineering skills from Artificial Intelligence and Computer Science
  • provide a programme of study that benefits from our research strengths across the disciplines
  • enable students to develop communication skills, initiative, professionalism and the ability to work independently as well as with others
  • provide graduates with the knowledge and skills necessary for their professional careers or for postgraduate study.

Programme outcomes: Knowledge and understanding

  • understand the principles and mechanisms underlying various kinds of intelligent processes
  • understand how to deal more effectively with natural intelligence using AI tools and techniques
  • understand how to represent and reason about knowledge in a computer
  • have an awareness of the philosophical issues that arise within Artificial Intelligence
  • have a knowledge and understanding of the principles of operation of computers from application programs down through system software to hardware and of computer networks
  • understand the concept of abstraction and its importance in the design of computer-based systems
  • understand the key aspects of the software development process
  • understand some of the underlying mathematical concepts used 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 systems
  • have an awareness of key issues in Artificial Intelligence and Computer Science that will continue to challenge researchers in the future

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

  • identify problems requiring a combination of techniques from both Artificial Intelligence and Computer Science
  • understand theoretical ideas and how they are realised in practice using computers
  • formulate appropriate assessment criteria and evaluate computer-based systems
  • apply principles of human-computer interaction to the evaluation and construction of systems

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

  • specify and design intelligent and traditional computer-based systems, using formal design procedures where appropriate
  • derive abstract representations and formulate appropriate solutions for problems

Programme outcomes: Graduate attributes - Skills and abilities in communication

  • work effectively as part of a team
  • provide and accept peer evaluation
  • 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

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

Programme outcomes: Technical/practical skills

  • develop and implement intelligent and traditional computer-based systems
  • use support tools from Artificial Intelligence and Computer Science 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.

Teaching and learning workload

You will learn through a mixture of scheduled teaching and independent study. Some programmes also offer work placements.

At Edinburgh we use a range of teaching and learning methods including lectures, tutorials, practical laboratory sessions, technical workshops and studio critiques.

The typical workload for a student on this programme is outlined in the table below, however the actual time you spend on each type of activity will depend on what courses you choose to study.

The typical workload for a student on this programme for each year of study
Start yearTime in scheduled teaching (%)Time in independant study (%)Time on placement (%)
Year 137630
Year 225750
Year 339610
Year 420800

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.

Assessment method balance

You will be assessed through a variety of methods. These might include written or practical exams or coursework such as essays, projects, group work or presentations.

The typical assessment methods for a student on this programme are outlined below, however the balance between written exams, practical exams and coursework will vary depending on what courses you choose to study.

The typical assessment methods for a student on this programme for each year of study
Start yearAssessment by written exams (%)Assessment by practical exams (%)Assessment by coursework (%)
Year 161831
Year 275025
Year 345055
Year 437063

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.

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