Bachelor of Science (BSc)
BSc Actuarial Science and Mathematics
Duration: 3 years
Year of entry: 2025
UCAS course code: NG31 / Institution code: M20
- Key features:
Scholarships available
Accredited course
- Typical A-level offer: A*AA including specific subjects
- Typical contextual A-level offer: A*AB including specific subjects
- Refugee/care-experienced offer: A*BB including specific subjects
- Typical International Baccalaureate offer: 37 points overall with 7,6,6 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 £34,500 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 and our Department funding pages .
Course unit details:
Coding Theory
| Unit code | MATH32031 |
|---|---|
| Credit rating | 10 |
| Unit level | Level 3 |
| Teaching period(s) | Semester 1 |
| Available as a free choice unit? | No |
Overview
Coding theory plays a crucial role in the transmission of information. Due to the effect of noise and interference, the received message may differ somewhat from the original message which is transmitted. The main goal of Coding Theory is the study of techniques which permit the detection of errors and which, if necessary, provide methods to reconstruct the original message. The subject involves some elegant algebra and has become an important tool in banking and commerce.
Pre/co-requisites
| Unit title | Unit code | Requirement type | Description |
|---|---|---|---|
| Groups and Geometry | MATH21120 | Pre-Requisite | Compulsory |
| Algebraic Structures 1 | MATH20201 | Pre-Requisite | Compulsory |
Aims
To introduce students to a subject of convincing practical relevance that relies heavily on results and techniques from Pure Mathematics.
Learning outcomes
On successful completion of this course unit students will be able to:
- state and prove fundamental theorems about error-correcting codes given in the course,
- calculate the parameters of given codes and their dual codes using standard matrix and polynomial operations,
- encode and decode information by applying algorithms associated with well-known codes,
- compare the error-detecting/correcting facilities of given codes for a given binary symmetric channel,
- design simple linear or cyclic codes with required properties,
- solve mathematical problems involving error-correcting codes by linking them to concepts from elementary number theory, combinatorics, linear algebra and elementary calculus.
Syllabus
- Introduction to the Main Problem of Coding Theory. [1 lecture]
- Hamming Distance. Code detection. Code correction. ISBN code. [2]
- Length and weight of a code. Perfect codes. [3]
- Linear codes. Generator matrices and standard forms. Encoding. Nearest neighbour decoding. [4]
- Dual code. Parity check matrix. Syndrome decoding. Incomplete decoding. [4]
- Hamming Codes and Decoding. [4]
- Finite fields. Cyclic codes. [4]
- Reed-Muller codes.
Assessment methods
| Method | Weight |
|---|---|
| Other | 20% |
| Written exam | 80% |
- Coursework: weighting 20%
- End of semester examination: weighting 80%
Feedback methods
Feedback tutorials will provide an opportunity for students' work to be discussed and provide feedback on their understanding. Coursework or in-class tests (where applicable) also provide an opportunity for students to receive feedback. Students can also get feedback on their understanding directly from the lecturer, for example during the lecturer's office hour.
Recommended reading
Recommended text:
R Hill, A First Course in Coding Theory, 1986, OUP.
Study hours
| Scheduled activity hours | |
|---|---|
| Lectures | 12 |
| Tutorials | 12 |
| Independent study hours | |
|---|---|
| Independent study | 76 |
Teaching staff
| Staff member | Role |
|---|---|
| Nikesh Solanki | Unit coordinator |
Additional notes
The independent study hours will normally comprise the following. During each week of the taught part of the semester:
• You will normally have approximately 60-75 minutes of video content. Normally you would spend approximately 2-2.5 hrs per week studying this content independently
• You will normally have exercise or problem sheets, on which you might spend approximately 1.5hrs per week
• There may be other tasks assigned to you on Blackboard, for example short quizzes or short-answer formative exercises
• In some weeks you may be preparing coursework or revising for mid-semester tests
Together with the timetabled classes, you should be spending approximately 6 hours per week on this course unit.
The remaining independent study time comprises revision for and taking the end-of-semester assessment.
The above times are indicative only and may vary depending on the week and the course unit. More information can be found on the course unit’s Blackboard page.