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AI masters online UK. 6 assessed courses, 1,800 notional hours, tuition-free.
Online or on campus
AI masters online UK. MSc Artificial Intelligence for Professionals at Haverton University: 8 assessed courses, 180 credits and 1,800 notional learning hours, at 10 hours per credit. The hours on each course add up to that total. Seminars run online. An London campus route is published separately from this online award. MSc Artificial Intelligence for Professionals is taught as one award, not a list of unrelated modules. The published length is 18 months, and the credit total is 180. Students move from Where a model helps and where it does not through Where a model helps and where it does not; Data for a model; Evaluation; Use in a workflow; Governance and the limit of the award; Capstone: applied AI file, and finish on Capstone: applied AI file. 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: Produce a professional file in Artificial Intelligence for Professionals Choose a method and write what the evidence cannot support Keep a record a third party can review 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.
Each credit is 10 notional learning hours. The courses add up to 180 credits and 1,800 hours.
Faculty spotlight
Haverton University supervises the courses and the final assessed file. Supervision is assigned from the school that owns the award.
Study online
Online tuition is free. Online examinations and certificates are 100% free and sponsored.
On-campus study
Prefer to learn at our London campus? Campus tuition is published on each programme page. All examinations are 100% free of charge.
| Code | Course | Credits · hours |
|---|---|---|
| S1CQO01 | Where a model helps and where it does not Where a model helps and where it does not (S1CQO01) is a course on MSc Artificial Intelligence for Professionals. It carries 20 credits and 200 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 20 · 200 h |
| S1DKN02 | Data for a model Data for a model (S1DKN02) is a course on MSc Artificial Intelligence for Professionals. It carries 20 credits and 200 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 20 · 200 h |
| SCQO581 | Questions, units, and data quality Questions, units, and data quality (SCQO581) is a course on MSc Artificial Intelligence for Professionals. It carries 20 credits and 200 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 20 · 200 h |
| SCQO582 | Statistical inference and a mistaken claim Statistical inference and a mistaken claim (SCQO582) is a course on MSc Artificial Intelligence for Professionals. It carries 20 credits and 200 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 20 · 200 h |
| SCQO583 | Machine learning, baselines, and leakage Machine learning, baselines, and leakage (SCQO583) is a course on MSc Artificial Intelligence for Professionals. It carries 40 credits and 400 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 40 · 400 h |
| Code | Course | Credits · hours |
|---|---|---|
| S1E4M04 | Use in a workflow Use in a workflow (S1E4M04) is a course on MSc Artificial Intelligence for Professionals. It carries 20 credits and 200 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 20 · 200 h |
| S1DUM05 | Governance and the limit of the award Governance and the limit of the award (S1DUM05) is a course on MSc Artificial Intelligence for Professionals. It carries 20 credits and 200 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 20 · 200 h |
| S1EOL06 | Capstone: applied AI file Capstone: applied AI file (S1EOL06) is a course on MSc Artificial Intelligence for Professionals. It carries 20 credits and 200 notional learning hours, at 10 hours per credit. The course is taught at master's level. Students compare a weaker method, judge the evidence, and state what the result does not show. The chapters are the syllabus. Each chapter is a class of work this course assesses. Preparation is the reading, dataset, or case for that chapter. Seminar time is spent on the decision, the calculation, or the draft. The student revises after feedback. A pass requires the method named in the chapters, evidence a marker can check, and a stated limit on what the result does not show. Haverton University teaches this course on the published route for this degree.
| 20 · 200 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 Haverton. 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. All online degree examinations and certificates are 100% free and sponsored — the only cost for online study is the application fee. Campus tuition and campus examinations are charged separately. Check the Fees page for details.
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. Haverton 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@haverton.org.
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