- UCAS course code
- GG14
- UCAS institution code
- M20
Bachelor of Science (BSc)
BSc Computer Science and Mathematics
Duration: 3 years
Year of entry: 2025
UCAS course code: GG14 / Institution code: M20
- Key features:
Scholarships available
- Typical A-level offer: A*A*A including specific subjects
- Typical contextual A-level offer: AAA including specific subjects
- Refugee/care-experienced offer: AAB including specific subjects
- Typical International Baccalaureate offer: 38 points overall with 7,7,6 at HL, including specific requirements
Fees and funding
Fees
Tuition fees for home students commencing their studies in September 2025 will be £9,535 per annum (subject to Parliamentary approval). Tuition fees for international students will be £36,000 per annum. For general information please see the undergraduate finance pages.
Policy on additional costs
All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).
Scholarships/sponsorships
The University of Manchester is committed to attracting and supporting the very best students. We have a focus on nurturing talent and ability and we want to make sure that you have the opportunity to study here, regardless of your financial circumstances.
For information about scholarships and bursaries please visit our undergraduate student finance pages .
Course unit details:
Cognitive Robotics
| Unit code | COMP34212 |
|---|---|
| Credit rating | 10 |
| Unit level | Level 3 |
| Teaching period(s) | Semester 2 |
| Available as a free choice unit? | Yes |
Overview
This unit provides an in-depth understanding of the field of cognitive robotics. This will analyse the selection, use and combination of methods and approaches in robotics, in artificial intelligence and in psychology and neuroscience to design intelligent behaviour and cognitive skills in interactive robots.
Aims
This unit provides an in-depth understanding of the field of cognitive robotics. This will analyse the selection, use and combination of methods and approaches in robotics, in artificial intelligence and in psychology and neuroscience to design intelligent behaviour and cognitive skills in interactive robots.
Learning outcomes
At the end of this course a student will be able to:
1. analyse the methods and software/hardware technologies for robotics research and applications
2. understand how our psychology and neuroscience understanding of behaviour and intelligence informs the
design of robotics models and applications
3. compare, select and apply different machine learning methods for intelligent behaviour in robots
4. Discuss the state of the art in cognitive and intelligent robotics models, and how this informs the design of future robot applications
5. Discuss the role of ethics and responsible research and innovation in robotics
Syllabus
Lecture topics: Introduction to Cognitive Robotics Overview of robot technologies, sensors and actuators Robot platforms Machine learning for robotics Developmental Robotics Neuro-robotics Evolutionary and swarm robotics Social robotics and human-robot interaction Language learning and speech interfaces Robot tutors for children Ethics for robotics and AIPractical Labs: The practical lab sessions will focus on the use of machine learning methods, such as deep learning, for robot vision and language and on the software tools for robotics.
Teaching and learning methods
16 Lectures and 4 labs
Employability skills
- Analytical skills
- Innovation/creativity
- Problem solving
- Research
- Written communication
Assessment methods
| Method | Weight |
|---|---|
| Written exam | 70% |
| Written assignment (inc essay) | 30% |
Feedback methods
Feedback on report and additional oral feedback during office/surgery hours and during labs.
Recommended reading
Cangelosi & Asada (2022), Cognitive Robotics. MIT Press.
Additional reading material provided in the online learning platform.
Study hours
| Scheduled activity hours | |
|---|---|
| Lectures | 16 |
| Practical classes & workshops | 8 |
| Independent study hours | |
|---|---|
| Independent study | 76 |
Teaching staff
| Staff member | Role |
|---|---|
| Angelo Cangelosi | Unit coordinator |