LoadingLoadingLoadingLoadingDual Master of Science (2 Degrees) — Conferred jointly with African Future University (AFU) & University of the Witwatersrand (Wits)
Université du Witwatersrand (Afrique du Sud)
Online only
Leveraging satellite remote sensing, predictive climate algorithms, agricultural telemetry, and machine learning to build sustainable African infrastructure. Students earn 2 independent accredited diplomas with a 60% / 40% international credit split. MSc Data Science & Climate Resilience (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 Data and measurement through Data and measurement; Models that can be checked; Deployment and care; Analytics project; Data and measurement (MSC-605); Models that can be checked (MSC-606), and finish on Models that can be checked (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 independent Master of Science diplomas upon completion Hands-on AI modeling on pan-African hydrological, drought, and agricultural datasets Supervised by leading African data scientists and earth observation experts 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 |
|---|---|---|
| MSC501 | Questions, units, and data quality Questions, units, and data quality (MSC501) is a course on MSc Data Science & Climate Resilience (Dual Award). 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. The degree is taught fully online.
| 20 · 200 h |
| MSC502 | Statistical inference and a mistaken claim Statistical inference and a mistaken claim (MSC502) is a course on MSc Data Science & Climate Resilience (Dual Award). 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. The degree is taught fully online.
| 20 · 200 h |
| MSC503 | Machine learning, baselines, and leakage Machine learning, baselines, and leakage (MSC503) is a course on MSc Data Science & Climate Resilience (Dual Award). 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. The degree is taught fully online.
| 20 · 200 h |
| Code | Course | Credits · hours |
|---|---|---|
| MSC504 | Evaluation, error analysis, and harm Evaluation, error analysis, and harm (MSC504) is a course on MSc Data Science & Climate Resilience (Dual Award). 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. The degree is taught fully online.
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| Code | Course | Credits · hours |
|---|---|---|
| MSC507 | Deployment, monitoring, and drift Deployment, monitoring, and drift (MSC507) is a course on MSc Data Science & Climate Resilience (Dual Award). 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. The degree is taught fully online.
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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 / French. 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. 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. African Future 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@afutureuni.com.
Recognised & Accredited
| 20 · 200 h |
| MSC505 | Data engineering and reproducible pipelines Data engineering and reproducible pipelines (MSC505) is a course on MSc Data Science & Climate Resilience (Dual Award). 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. The degree is taught fully online.
| 20 · 200 h |
| MSC506 | Responsible use, governance, and human review Responsible use, governance, and human review (MSC506) is a course on MSc Data Science & Climate Resilience (Dual Award). 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. The degree is taught fully online.
| 20 · 200 h |
| 20 · 200 h |
| MSC508 | Capstone: a method, a result, and the limitation Capstone: a method, a result, and the limitation (MSC508) is a course on MSc Data Science & Climate Resilience (Dual Award). 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. The degree is taught fully online.
| 40 · 400 h |