LoadingLoadingLoadingLoadingMaster data science en ligne. 6 cours, 1,800 heures, sans frais de scolarité.
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Master data science en ligne. Master Science des données à Université Africaine du Futur : 6 cours, 180 crédits et 1,800 heures d'apprentissage notionnel, à raison de 10 heures par crédit. Les heures indiquées sur chaque cours font exactement ce total. Le diplôme est entièrement en ligne. Il n'y a pas de campus à rejoindre. Master Science des données is taught as one award, not a list of unrelated modules. The published length is 18 mois, and the credit total is 180. Students move from Question, mesure et données douteuses through Question, mesure et données douteuses; Analyse et ce qu'elle autorise; Tableau de bord; Responsabilité des données; Note à un non-spécialiste; Projet : dossier d'analyse, and finish on Projet : dossier d'analyse. Each course has a question, a method, and a submission. In this field, students apply the method of the subject to a defined problem and defend the result. Reading is a core text, a case or dataset, and a critique. The artefact a marker expects is a submission that shows the method, the evidence, and the limit of the claim. The award is built so that a graduate can do the following in practice: Produire un dossier professionnel en Science des données Choisir une méthode et écrire ce que la preuve ne permet pas Tenir un dossier qu'un tiers peut relire 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.
Chaque crédit vaut 10 heures d'apprentissage notionnel. L'addition des cours fait 180 crédits et 1,800 heures.
Faculty spotlight
Université Africaine du Futur encadre les cours et le dossier final. L'encadrement est assuré par l'école qui porte le diplôme.
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Tuition is free. Examinations are free. There is no exam fee. Study from anywhere in the world.
| Code | Course | Credits · hours |
|---|---|---|
| SGW1L01 | Question, mesure et données douteuses Question, mesure et données douteuses (SGW1L01) is a 30-credit course on Master Science des données, with 300 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Question, mesure et données douteuses 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 core text, a case or dataset, and a critique. Seminar time is for the decision, not for reading the materials aloud. Assessment is a submission that shows the method, the evidence, and the limit of the claim. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
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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 mois. Teaching language: French. Actual time-to-complete depends on mode and any recognised prior learning.
Recognised & Accredited
| 30 · 300 h |
| SGM1Z02 | Analyse et ce qu'elle autorise Analyse et ce qu'elle autorise (SGM1Z02) is a 30-credit course on Master Science des données, with 300 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Analyse et ce qu'elle autorise 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 core text, a case or dataset, and a critique. Seminar time is for the decision, not for reading the materials aloud. Assessment is a submission that shows the method, the evidence, and the limit of the claim. 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 |
| SGC2D03 | Tableau de bord Tableau de bord (SGC2D03) is a 30-credit course on Master Science des données, with 300 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Tableau de bord 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 core text, a case or dataset, and a critique. Seminar time is for the decision, not for reading the materials aloud. Assessment is a submission that shows the method, the evidence, and the limit of the claim. 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 |
| Code | Course | Credits · hours |
|---|---|---|
| SG22S04 | Responsabilité des données Responsabilité des données (SG22S04) is a 30-credit course on Master Science des données, with 300 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Responsabilité des données 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 core text, a case or dataset, and a critique. Seminar time is for the decision, not for reading the materials aloud. Assessment is a submission that shows the method, the evidence, and the limit of the claim. A pass requires a clear method, evidence a marker can check, and an explicit limit. Credit is not awarded for summary alone.
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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. 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.
| 30 · 300 h |
| SFS3605 | Note à un non-spécialiste Note à un non-spécialiste (SFS3605) is a 30-credit course on Master Science des données, with 300 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Note à un non-spécialiste 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 core text, a case or dataset, and a critique. Seminar time is for the decision, not for reading the materials aloud. Assessment is a submission that shows the method, the evidence, and the limit of the claim. 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 |
| SFI3K06 | Projet : dossier d'analyse Projet : dossier d'analyse (SFI3K06) is a 30-credit course on Master Science des données, with 300 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Projet : dossier d'analyse 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 core text, a case or dataset, and a critique. Seminar time is for the decision, not for reading the materials aloud. Assessment is a submission that shows the method, the evidence, and the limit of the claim. 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 |