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Computing taught as systems you can build and explain
Online or on campus
Computer science at Brigant is about systems a student can specify, test, and hand over. Examples come from services used in the UK: payments, health records, and public websites. You are marked on the artefact and on the explanation of its limits. The degree is taught online, with campus access in Edinburgh for students on that pathway. MSc Computer Science is taught as one award, not a list of unrelated modules. The published length is 24 months, and the credit total is 36. Students move from Advanced Algorithms & Data Structures through Advanced Algorithms & Data Structures; Software Engineering & Architecture; Database Systems & Distributed Data; Computer Networks & Cloud Computing; Artificial Intelligence & Machine Learning; Secure Systems & Cryptography, and finish on MSc Dissertation / Capstone Project. Each course has a question, a method, and a submission. In this field, students specify a small system, show how it was tested, and state how it fails. Reading is a specification, a test note, and an incident or post-mortem. The artefact a marker expects is a specification or reviewed component with tests and a trade-off note. The award is built so that a graduate can do the following in practice: Specify a small system and its interfaces Test a component and report the failure Describe how the system would be deployed and recovered Teaching assumes the student can read a source, attempt a problem before the seminar, and revise after feedback. Attendance at live seminars is part of the design. The capstone or final course must use the methods of the earlier courses; a project that ignores them does not pass. The pages for each course name the topics that are examined. Those topics are the syllabus. A brochure line is not a substitute for them.
Credit hours on this page are the sum of the modules. Online tuition is covered. Examination or administrative fees may still apply. Campus study, where it is offered, is priced separately.
Faculty spotlight
The school of computing at the University of Brigant supervises the computing modules and the project.
Study online
Online tuition is free. Online examinations are free. There is no exam fee for online study.
On-campus study
Prefer to learn at our Edinburgh campus? Campus tuition and campus examinations are charged. The published campus price is on each programme page.
| Code | Course | Credits · hours |
|---|---|---|
| CS501 | Advanced Algorithms & Data Structures Advanced Algorithms & Data Structures (CS501) is a 3-credit course on MSc Computer Science, with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Advanced Algorithms & Data Structures as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| CS502 | Software Engineering & Architecture Software Engineering & Architecture (CS502) is a 3-credit course on MSc Computer Science, with 30 notional learning hours. By the end, students can draw the system, name the constraint that binds it, and compare two responses, using Software Engineering & Architecture as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a system description, an indicator note, and a project option paper. Seminar time is for the decision, not for reading the materials aloud. Assessment is a recommendation for one decision, with the evidence and the downside. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone. This course does not confer a professional engineering licence.
| 3 · 30 h |
| CS503 | Database Systems & Distributed Data Database Systems & Distributed Data (CS503) is a 3-credit course on MSc Computer Science, with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Database Systems & Distributed Data as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| CS504 | Computer Networks & Cloud Computing Computer Networks & Cloud Computing (CS504) is a 3-credit course on MSc Computer Science, with 30 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using Computer Networks & Cloud Computing as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| Code | Course | Credits · hours |
|---|---|---|
| CS505 | Artificial Intelligence & Machine Learning Artificial Intelligence & Machine Learning (CS505) is a 3-credit course on MSc Computer Science, with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Artificial Intelligence & Machine Learning as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| CS506 | Secure Systems & Cryptography Secure Systems & Cryptography (CS506) is a 3-credit course on MSc Computer Science, with 30 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using Secure Systems & Cryptography as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| CS507 | Human–Computer Interaction Human–Computer Interaction (CS507) is a 3-credit course on MSc Computer Science, with 30 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using Human–Computer Interaction as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| CS508 | Research Methods in Computing Research Methods in Computing (CS508) is a 3-credit course on MSc Computer Science, with 30 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using Research Methods in Computing as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| Code | Course | Credits · hours |
|---|---|---|
| CS601 | Distributed Systems & Scalability Distributed Systems & Scalability (CS601) is a 3-credit course on MSc Computer Science, with 30 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using Distributed Systems & Scalability as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| CS602 | Advanced Topics in AI (elective) Advanced Topics in AI (elective) (CS602) is a 3-credit course on MSc Computer Science, with 30 notional learning hours. By the end, students can define a measurable question, fit a method that can be checked, and report where it fails, using Advanced Topics in AI (elective) as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a dataset description, a methods note, and one published evaluation. Seminar time is for the decision, not for reading the materials aloud. Assessment is a project note with the question, the method, the result, and the limitation. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 3 · 30 h |
| CS603 | MSc Dissertation / Capstone Project MSc Dissertation / Capstone Project (CS603) is a 6-credit course on MSc Computer Science, with 60 notional learning hours. By the end, students can specify a small system, show how it was tested, and state how it fails, using MSc Dissertation / Capstone Project as the working context rather than a generic management example. The course is taught in three movements. First, students establish the terms and the decision the course is about. Second, they apply the method to a case, dataset, text, or design and compare it with a weaker alternative. Third, they revise the work after feedback and state what the conclusion cannot support. Preparation uses a specification, a test note, and an incident or post-mortem. Seminar time is for the decision, not for reading the materials aloud. Assessment is a specification or reviewed component with tests and a trade-off note. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
| 6 · 60 h |
Modules are assessed through a published mix of coursework, applied projects, and examinations. Exam windows are announced in advance so students in other time zones are not forced into overnight sittings. Alternative arrangements are available where documented.
The published duration is 24 months. Teaching language: English. Actual time-to-complete depends on mode and any recognised prior learning.
You may study this award fully online from your country, or — where published — on campus at Brigant. Online study does not require a student visa. Campus study may.
Degree tuition for this award is published as £0 / tuition-free on the online pathway. Examination or administrative fees may apply at checkout — never an annual tuition invoice. Check the Fees page for any extras.
Requirements are grouped on this page (academic, English, documents). Equivalent qualifications are considered. English may be waived after prior English-medium study.
Assessment is typically a mix of coursework, projects, and examinations. Doctoral awards include a thesis or dissertation and an oral examination. Details sit in the programme specification and module outlines.
Recognition of the award for local employment, professional licence, or ministry attestation is decided by your employer or regulator. University of Brigant publishes verification pages for certificates. We do not claim automatic equivalence in every country.
Start an application on this website. Progress is saved from the first step. Admissions: admissions@brigant.uk.
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