Undergraduate Course: Informatics 1 - Cognitive Science (INFR08020)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 8 (Year 1 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course is designed as a first introduction to Cognitive Science, the interdisciplinary study of the mind and how it processes information. It will provide a selective but representative overview of the subject, suitable for all interested students, including students in Informatics as well as external students.
While the specifics covered in a given year may vary, the course generally covers basic approaches in cognitive science (e.g., theories, models, research methods) as well as topics such as language, vision, learning, memory, neuroscience, and societal impacts. The course emphasizes computational perspectives, and course activities will include learning about and working with simple computational models of selected cognitive phenomena. |
| Course description |
The syllabus covers a variety of topics across the breadth of cognitive science. A list of typical topics is given below. The specific selection and organisation of topics in a given year may vary.
- Fundamentals of cognitive science, including representations, processes, theories, models, research methods, and interdisciplinary perspectives
- Language, including language properties, language acquisition in children, and computational models of language
- Vision, including the anatomy of vision, neural correlates of visual perception, and comparisons of biological and artificial visual systems
- Learning, including types of human and machine learning (supervised, unsupervised, and reinforcement learning, perceptrons, neural networks), and studies of human learning
- Memory, including types of memory, concepts and categories, memory impairments, and computational models of memory
- Neuroscience, including basic brain anatomy and function, experimental techniques to record brain activity, and models of neurons
- Cognitive science and society, including influences of culture on cognition, famous case studies in cognitive science, controversies, research ethics, professional responsibility, and both positive and negative impacts and applications
- Additional topics, such as (for example): AI and philosophy, animal cognition, creativity, education, evolution, neurodiversity, reasoning, social cognition, infant learning, etc
Note that this course is intended to give a high-level introduction to a selection of topics in cognitive science; subsequent courses (e.g., Computational Cognitive Science) will then provide a more detailed coverage.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | This course does not assume prior programming skills, but students are required to learn how to code. There will be no explicit instruction on programming in lectures. Students will receive an introduction to a contemporary programming language (like Python) in the labs and use it to experiment with simple cognitive models in the assignments. While there are resources provided in labs, some students with no prior programming / maths experience have reported difficulty completing the assignments. |
Information for Visiting Students
| Pre-requisites | This is a first-year course; students are expected to have an academic profile equivalent to our entrance requirements. The required subjects for this course are an equivalent to Scottish Higher Mathematics at A.
This course does not assume prior programming skills, but students are required to learn how to code. There will be no explicit instruction on programming in lectures. Students will receive an introduction to a contemporary programming language (like Python) in the labs and use it to experiment with simple cognitive models in the assignments. While there are resources provided in labs, some students with no prior programming / maths experience have reported difficulty completing the assignments. |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2026/27, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 30,
Seminar/Tutorial Hours 10,
Supervised Practical/Workshop/Studio Hours 10,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
146 )
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| Assessment (Further Info) |
Written Exam
60 %,
Coursework
40 %,
Practical Exam
0 %
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| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Minutes |
|
| Main Exam Diet S2 (April/May) | Informatics 1 - Cognitive Science (INFR08020) | 120 | | | Resit Exam Diet (August) | Informatics 1 - Cognitive Science (INFR08020) | 120 | |
Learning Outcomes
On completion of this course, the student will be able to:
- demonstrate knowledge of key areas of cognitive science, with a focus on integrated, interdisciplinary perspectives
- evaluate important conceptual problems in cognitive science and solutions that have been proposed
- analyse and modify simple computational models of selected cognitive phenomena
- give examples of how cognitive science is societally situated and of ethical issues raised in research and applications
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Reading List
| https://opencourse.inf.ed.ac.uk/inf1-cg |
Contacts
| Course organiser | Dr Matthias Hennig
Tel: (131 6)50 3080
Email: m.hennig@ed.ac.uk |
Course secretary | Ms Kendal Reid
Tel: (0131 6)50 5194
Email: kr@inf.ed.ac.uk |
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