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BSc Artificial Intelligence and Mathematics

BSc Artificial Intelligence and Mathematics Degree Programme Table

1. Awarding Institution: University of Edinburgh

2. Teaching Institution: University of Edinburgh

3. Programme Accredited By: see accreditation pages

4. Final Award: BSc Honours

5. Programme Title: Artificial Intelligence and Mathematics (BSc)

6. UCAS Code: GG17

7. Relevant QAA subject benchmarking: Computing. Mathematics.

8. Mode of study: Full time

9. Educational aims of programme:

Artificial intelligence (AI) 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. In recent years AI has become more mathematical. AI researchers have been extracting neat techniques from their "scruffy" programs and formalizing them using mathematics. New uses are being found for mathematics in every area of AI and where existing mathematics is not up to the task, new kinds of mathematics are being invented. The Artificial Intelligence and Mathematics degree programme aims to reflect these developments.

The rest of this document focuses on the Artificial Intelligence part of this joint degree programme. The Degree Programme Specification for Mathematics (BSc) has more details on the Mathematics part of the programme.

Principal aims:
  • introduce students to AI and to the kind of mathematics required to formalize and understand AI techniques
  • develop students who are well equipped to develop robust AI programs, to extend AI techniques to new problems, and to apply AI within mathematics
  • to develop graduates possessing a thorough understanding of the scope and limitations of artificial intelligence, both theoretically and practically
  • to provide a programme of study that benefits from our research strengths across AI
  • to enable students to develop communication skills, initiative, professionalism and the ability to work independently as well as with others
  • to provide graduates with the knowledge and skills necessary for both academic and industrial research and development.

10. Programme Outcomes

The programme provides opportunities for learners to achieve the following outcomes:

(a) Knowledge and understanding

On completing the programme students should:

  • 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
  • understand the role that mathematics has in artificial intelligence
  • have an awareness of the philosophical issues that arise within artificial intelligence
  • have an awareness of key issues in artificial intelligence that will continue to challenge researchers in the future.

(b) Intellectual skills

On completing the programme students should have the ability to:

  • specify and design intelligent computer-based systems
  • derive abstract representations and formulate appropriate solutions for problems
  • use mathematics to model and understand intelligent processes
  • understand theoretical ideas and how they are realised in practice using computers.

(c) Professional/subject/specific/practical skills

On completing the programme students should have the ability to:

  • develop and implement intelligent computer-based systems
  • use support tools from artificial intelligence and mathematical skills during the development process
  • formulate appropriate assessment criteria and evaluate intelligent computer-based systems
  • apply principles of human-computer interaction to the evaluation and construction of systems.

(d) Transferable skills

On completing the programme students should have the ability to:

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

11. Programme Structure and Features

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

12. Entry Requirements:

Please consult the current University Undergraduate Prospectus.

13. Degree Classification

The final degree classification 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%, 40%. Students who fail final year can be awarded an Ordinary Degree on the basis of their third year marks.