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Dual US Master of Science (2 Degrees) — Conferred jointly with Frontier Innovation University (USA) & Arizona State University Network (USA)
Arizona State University (United States)
Online or on campus
Designed for technology executives and AI researchers developing green computing frameworks, ethical AI governance, and scalable autonomous tech. Students earn 2 independent accredited diplomas with a 60% / 40% international credit split. MSc Sustainable Innovation & AI Systems (Dual Award) is taught as one award, not a list of unrelated modules. The published length is 18 months, and the credit total is 36. Students move from The system in view through The system in view; Measurement; Projects and risk; Applied project; The system in view (MSC-605); Measurement (MSC-606), and finish on Measurement (MSC-606). 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 Master of Science degrees upon graduation Capstone projects targeted at smart infrastructure and energy innovation Affordable per-semester installment schedule 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.
Complete your MSc Sustainable Innovation & AI Systems (Dual Award) fully online from anywhere in the world with faculty-led modules and flexible scheduling.
Attend seminars and access facilities in person at Frontier Innovation University. Campus tuition and campus examinations are charged.
| Code | Course | Credits · hours |
|---|---|---|
| MSC-601 | The system in view The system in view (MSC-601) is a 6-credit course on MSc Sustainable Innovation & AI Systems (Dual Award), with 60 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 The system in view 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.
| 6 · 60 h |
| MSC-602 | Measurement Measurement (MSC-602) is a 6-credit course on MSc Sustainable Innovation & AI Systems (Dual Award), with 60 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 Measurement 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.
| 6 · 60 h |
| MSC-603 | Projects and risk Projects and risk (MSC-603) is a 6-credit course on MSc Sustainable Innovation & AI Systems (Dual Award), with 60 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 Projects and risk 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.
| 6 · 60 h |
| Code | Course | Credits · hours |
|---|---|---|
| MSC-604 | Applied project Applied project (MSC-604) is a 6-credit course on MSc Sustainable Innovation & AI Systems (Dual Award), with 60 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 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 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.
| 6 · 60 h |
| MSC-605 | The system in view (MSC-605) The system in view (MSC-605) (MSC-605) is a 6-credit course on MSc Sustainable Innovation & AI Systems (Dual Award), with 60 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 The system in view (MSC-605) 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.
| 6 · 60 h |
| Code | Course | Credits · hours |
|---|---|---|
| MSC-606 | Measurement (MSC-606) Measurement (MSC-606) (MSC-606) is a 6-credit course on MSc Sustainable Innovation & AI Systems (Dual Award), with 60 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 Measurement (MSC-606) 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.
| 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 18 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 Frontier. 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. Frontier Innovation 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@frontuni.com.
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