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MA (Honours) Linguistics and Artificial Intelligence

MA (Hons) Linguistics and Artificial Intelligence Degree Programme Table

This document focuses on details of the AI component of this joint degree. For more details of the Linguistics component, please refer to the degree programme specifications of the School of Philosophy, Psychology and Language Sciences within the College of Humanities and Social Sciences.

1. Awarding Institution: University of Edinburgh

2. Teaching Institution: University of Edinburgh

3. Programme Accredited By: see accreditation pages

4. Final Award: MA Honours

5. Programme Title: MA (Hons) Linguistics and Artificial Intelligence

6. UCAS Code: QG17

7. Relevant QAA subject benchmarking: Computing. Linguistics.

8. Mode of Study: Full time

9. Educational aims of programme:

The Linguistics and AI degree brings together the two main disciplines that are relevant to the study of Computational Linguistics, the activity of designing and building computer systems that can perform tasks like natural language understanding, production and translation. Converting a theoretical idea into a computer implementation is rarely a trivial task - it requires the original theory to be very precisely specified and it requires new issues such as computational efficiency to be addressed. AI provides many of the necessary concepts to aid in this transition. On the other hand, to be modular and extensible, computer language processing systems need to be based on a firm understanding of the relevant linguistic phenomena and the generalisations that can be made about them. The Artificial Intelligence and Linguistics degree programme aims to reflect the interdependence of the two disciplines in this area.

The principal aims of this course are to:

  • introduce students to the methods used in both AI and Linguistics
  • develop students who are well equipped to develop robust programs, to extend AI techniques to new problems, especially within Linguistics
  • develop students' understanding of the theoretical and practical issues in Linguistics, and to equip them with the skill to carry out independent empirical research
  • to develop graduates possessing a thorough understanding of the scope and limitations of Computational Linguistics, both theoretically and practically
  • to provide a programme of study that benefits from our research strengths across AI and Linguistics
  • 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 the learners to achieve the following outcomes:

(a) Knowledge and understanding

On completing the programme students should be able to:

  • understand the principles and mechanisms underlying various kinds of intelligent processes, both in humans and machines
  • understand how to deal more effectively with natural languages using AI tools and techniques
  • understand how to represent and reason about knowledge in a computer
  • have a good understanding of the broad range of issues studies in Linguistics
  • have an awareness of the philosophical issues that arise within Artificial Intelligence and Linguistics
  • be equipped with the basic skills to carry out independent research in Computational Linguistics.

(b) Intellectual skills

On completing the programme students should have the ability to:

  • specify and design intelligent computer-based language systems
  • derive abstract representations and formulate appropriate solutions for problems
  • use Artificial Intelligence to model and understand intelligent processes and natural language problems
  • understand the theory and practice of both Linguistics and Artificial Intelligence, and how computational modeling is used in the understanding of natural language.

(c) Professional/subject/specific/practical skills

and also the ability to:

  • develop and implement intelligent computer-based systems
  • understand and evaluate empirical studies presented in scientific research papers
  • formulate appropriate assessment criteria and evaluate intelligent computer-based 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%.