Information on the Cognitive Science specialist area.
The Cognitive Science specialist area gives students an opportunity to study the structure and behaviour of both natural and artificial cognitive systems. Relevant cognitive processes include language, reasoning, vision, and learning, which can be studied from neural, psychological, probabilistic, and symbolic viewpoints. Students are encouraged to also take courses from the School of Philosophy, Psychology and Language Sciences (PPLS); see the optional external courses list below.
Edinburgh is one of the birthplaces of Cognitive Science, with great strengths in all its constituent disciplines. Students wishing to continue as academics find a Cognitive Science MSc an invaluable opportunity to “jump tracks” into a new area or topic. For instance, students with mathematical or computing backgrounds may learn to work on one of the fascinating problems found in brain/cognitive research. A range of academic departments employ people with a “Cognitive” background or specialism, from the purely computational through to Psychology and to more applied fields such as Design.
How can I best prepare for the specialist courses?
The courses in this specialist area vary in terms of which programming languages are used, with Matlab and Python being most common.
If you are planning to take any courses in natural language processing and haven't programmed in Python before, we recommend you start to learn it before you arrive. Find an online (or local college) tutorial at your level. The Computer Programming for Speech and Language Processing starts from scratch, but learning to program well takes time: starting early will help, and will leave you more time to devote to other aspects of the programme.
Depending on the courses you choose, the level of required mathematical knowledge can vary widely. Nevertheless, the most common refrain we hear from students is "I wish I had spent more time preparing for the maths I would need."
At a minimum, to prepare for the core semester 1 courses you should go through the material on Sharon Goldwater's maths preparation page, which covers important basics including probability theory. This will prepare you for the Semester 1 core course Computational Cognitive Science, as well as the popular Accelerated Natural Language Processing course.
Other courses may require additional knowledge (especially of linear algebra); if you click on the course link below you should see these requirements listed in the "other requirements" box of the course descriptor.
What courses should I take?
We recommended selecting at least fifty credit points from the courses below. While most students should take the core course, you can omit this course if you already have most of the material in your background.
The notes below the tables provide a rough guide to the background required for each course, but please click through to check the "other requirements" in the descriptor of each course to be sure it is suitable for you.
|Semester 1||Semester 2|
Computational Cognitive Science (level 10)
|Optional Courses (see notes below)|
Automated Reasoning (level 9)
Accelerated Natural Language Processing (20 credits)
Introductory Applied Machine Learning (20 credits)
Machine Learning and Pattern Recognition (20 credits)
Machine Learning Practical (20 credits, full year)
|Further Optional Courses (see notes below)|
Origins and Evolution of Language (20 credits)
Psycholinguistics (20 credits)
Theories of Mind (20 credits)
Simulating Language (20 credits)
Notes on programming courses
If you are doing language-related courses, we recommend taking Computer Programming for Speech and Language Processing to fulfill the programming requirement for the degree rather than another course (such as Introduction to Java Programming).
Notes on Optional Courses
These courses are mainly from the School of Informatics, with a few from the School of Philosophy, Psychology, and Language Sciences (PPLS) that are more computationally oriented.
Not all optional courses are appropriate for all students on the Cognitive Science degree. Generally, the language processing, cognition, and HCI courses have lower maths and programming requirements and should be suitable for all students (but you should still do some preparation--see Maths and Programming preparation sections above). Neuroscience, machine learning, robotics, and other courses are typically more challenging in terms of maths, programming, or both. If you click on the course link below you should see these requirements listed in the "other requirements" box of the course descriptor.
Notes on Further Optional Courses
These courses are offered by the School of Philosophy, Psychology and Language Sciences (PPLS), as part of their MSc degrees. They can be good choices for some students but please keep in mind the following:
- These courses often differ from Informatics courses in their study patterns and number of contact hours. Some of them only run for half the semester (a single "teaching block").
- Many courses list no formal prerequisites, but may still assume some background in the discipline to prepare you for the assessment. For example, some courses are assessed by an essay, which may assume some familiarity with academic writing of the appropriate style. If in doubt about your suitability, check with the course organiser.
- You should register as early as possible for these courses. They can have limited numbers, earlier deadlines than Informatics, and course materials on Learn are only available after registering.
The Further Optional Courses above are a selection of the most relevant courses from PPLS. A complete list can be found on the DRPS pages for PPLS.
Informatics course timetable