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MSc Artificial Intelligence

MSc Artificial Intelligence (Full time) Degree Programme Table

MSc Artificial Intelligence (Part time) 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: MSc/Diploma in Artificial Intelligence

5. Programme Title: MSc in Artificial Intelligence

6. UCAS Code: not relevant

7. Relevant QAA subject benchmarking: Computing

8. Mode of Study: Normally full time. Suitably qualified candidates may be permitted to study for an MSc on a part-time basis over a maximum period of three years. Part-time students must satisfy the same course requirements as full-time students. Subject to timetabling constraints, locally resident part-time candidates will normally take two lecture courses per semester, which typically requires attendance for one and a half days per week. Part time candidates resident elsewhere are required to study full-time for one semester (thirteen weeks) per year. A candidate whose work is judged to be satisfactory may be permitted to pursue his/her project work at their sponsoring company during his/her third year, subject to satisfactory supervision arrangements being made.

9. Educational aims of programme:

This degree is aimed at training graduates so that they can become active practitioners in the field of Artificial Intelligence. The emphasis is on practical techniques for the design and construction of intelligent systems, enabling graduates from this course to apply their skills in a variety of settings. Students also have some opportunity to gain a working knowledge of conventional computer science, cognitive science and other associated subjects by taking appropriate courses.

The principal aims of the degree are to:

  • Develop graduates possessing a thorough understanding of one specialist area of Artificial Intelligence;
  • Equip students with advanced computer-based scientific and engineering skills;
  • Provide a programme of study that benefits from our research strengths in Artificial Intelligence;
  • Enable students to develop communication skills, initiative, professionalism and the ability to work independently as well as with others; and
  • Provide graduates with the knowledge and skills necessary for professional careers or for postgraduate research.

10. Programme Outcomes

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

(a) Knowledge and Understanding

  • Understand the process of building computational systems in all its stages and be able to demonstrate this understanding in supervised system building efforts.
  • Have advanced knowledge of the state of the art in an AI research area. The exact specialisms available vary over time, but generally fall in the areas of: robotics, AI reasoning, machine learning and natural language processing.
  • Understand Informatics research methodologies at a level that permits the student to engage in future doctoral research.
  • Know the main research methodologies used in Informatics.

(b) Intellectual Skills

The ability to:

  • Develop literature review and analysis skills.
  • Specify a research question and identify the relevant background literature.

(c) Professional/Subject/Specific/Practical Skills

The ability to:

  • Develop project skills.
  • Develop proposal writing skills.
  • Undertake a substantive project (4–5 months) on the proposed topic.
  • Write an extended research-style report.

(d) Transferable Skills

  • Deploy logical, analytical, and problem solving skills and to synthesise solutions.
  • Show self-direction and time management skills when working independently.
  • Develop skills needed for undertaking extended projects, including reviews, time management and writing extended reports.
  • 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.
  • The ability to work effectively with people from different cultural contexts.
  • The ability to work to strict deadlines and employ effective time management.

11. Programme Structure and Features

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

The year consists of two components: (1) about 7 months of coursework in 2 semesters and (2) about 5 months of project work leading to a dissertation. During the taught part of the course, September to April, students attend lectures, tutorials and group practicals and acquire the theoretical foundation to enable students to engage in independent research. Between May and August, students get the opportunity to make a practical application of their knowledge by undertaking a major individual research project on which they write a dissertation. The project is normally supervised by a member of academic staff as one of his/her research interests, with assistance from his/her research team.

Teaching and learning methods include traditional lecture-style teaching, interactive sessions (tutorials and seminars), practical work (labs, supervised practical sessions, coursework) and supervised, self-directed study (private study, preparation of literature reviews, research proposals, dissertation preparation). Coursework is submitted periodically throughout the semesters. Exams on the coursework normally occur at the end of semesters 1 and 2. Students need to achieve an average from the combined exam and coursework results of at least 50% to proceed to the dissertation phase. Those with an average of at least 40% exit with a Diploma and those below 40% Fail.

Each student selects from a list of specialisms. The courses that the student attends will be constrained by the specialism. Some courses will be required and all specialisms also allow some free choices. More information can be found in the MSc course guide.

Entry Requirements:

Students should have a first or upper second class honours degree or its equivalent, and in an area of Informatics, such as Artificial Intelligence, Cognitive Science or Computer Science. Students should also have experience in computer programming.

Applicants with degrees in these disciplines will also be considered: Education, Electrical Engineering, Psychology, Mathematics, Philosophy and Physics.

Overseas applicants will be required to show evidence of sufficient competence in written and spoken English.

12. Degree Classification

There are three possible degree classifications:

  1. MSc with Distinction: requires an average of at least 70% across all taught courses and a dissertation mark of at least 70%;

  2. MSc: average of at least 50% across all taught courses and a dissertation mark of at least 50%

  3. Diploma: average of at least 40% across all taught courses.

Last Revised: Ian Stark, September 2008