LoadingLoadingLoadingLoadingDual Transatlantic Bachelor's Degree (2 Diplomas) — Conferred jointly with GlobalMind University (GMU) & Arizona State University (USA)
Arizona State University (United States)
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An innovative undergraduate curriculum integrating modern full-stack development, cloud microservices, and applied AI systems. Students earn 2 independent accredited diplomas with a 65% / 35% international credit split. BSc Software Engineering & Applied AI (Dual Award) is taught as one award, not a list of unrelated modules. The published length is 36 months, and the credit total is 120. Students move from Software Systems Design, Requirements & Interfaces through Software Systems Design, Requirements & Interfaces; Full-Stack Programming, Testing & Code Quality; Cloud Microservices, DevOps & Reliability; Applied AI Systems Engineering Project (ASU Partner); Software Engineering Capstone & Dual-Award Defence, and finish on Software Engineering Capstone & Dual-Award Defence. Each course has a question, a method, and a submission. In this field, students define a measurable question, fit a method that can be checked, and report where it fails. Reading is a dataset description, a methods note, and one published evaluation. The artefact a marker expects is a project note with the question, the method, the result, and the limitation. The award is built so that a graduate can do the following in practice: Two official Bachelor of Science degree certificates upon graduation American innovation methodology and global tech industry competencies Direct pathway into Transatlantic Executive Master's and MBA pathways 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.
Study online
Tuition is free. Examinations are free. There is no exam fee. Study from anywhere in the world.
| Code | Course | Credits · hours |
|---|---|---|
| BSC-D101 | Software Systems Design, Requirements & Interfaces Software Systems Design, Requirements & Interfaces (BSC-D101) is a 20-credit course on BSc Software Engineering & Applied AI (Dual Award), with 200 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 Software Systems Design, Requirements & Interfaces 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.
| 20 · 200 h |
| BSC-D102 | Full-Stack Programming, Testing & Code Quality Full-Stack Programming, Testing & Code Quality (BSC-D102) is a 20-credit course on BSc Software Engineering & Applied AI (Dual Award), with 200 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 Full-Stack Programming, Testing & Code Quality 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.
| 20 · 200 h |
| BSC-D103 | Cloud Microservices, DevOps & Reliability Cloud Microservices, DevOps & Reliability (BSC-D103) is a 20-credit course on BSc Software Engineering & Applied AI (Dual Award), with 200 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 Cloud Microservices, DevOps & Reliability 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.
| 20 · 200 h |
| Code | Course | Credits · hours |
|---|---|---|
| BSC-D201 | Applied AI Systems Engineering Project (ASU Partner) Applied AI Systems Engineering Project (ASU Partner) (BSC-D201) is a 30-credit course on BSc Software Engineering & Applied AI (Dual Award), with 300 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 Applied AI Systems Engineering Project (ASU Partner) 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.
| 30 · 300 h |
| BSC-D202 | Software Engineering Capstone & Dual-Award Defence Software Engineering Capstone & Dual-Award Defence (BSC-D202) is a 30-credit course on BSc Software Engineering & Applied AI (Dual Award), with 300 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 Software Engineering Capstone & Dual-Award Defence 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.
| 30 · 300 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 36 months. Teaching language: English. Actual time-to-complete depends on mode and any recognised prior learning.
This is a fully online award. You study from your country. No student visa and no campus relocation are required.
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. GlobalMind University 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@gmuniv.com.
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