LoadingLoadingLoadingLoadingThis award is taught and assessed in French. It is not the English-medium MBA or master's with the same subject. Open the French prospectus.
Données administratives et enquêtes — cours et soutenance en français.
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Question, jeu de données, modèle simple, limite. Cas administrations et enquêtes. Code commenté en français. Ce n'est pas un titre d'ingénieur d'État. Master Science des données appliquée is taught as one award, not a list of unrelated modules. The published length is 24 mois, and the credit total is 48. Students move from Statistique inférentielle through Statistique inférentielle; Programmation pour les données; Qualité des données; Visualisation responsable; Apprentissage supervisé — prudence; Mémoire, and finish on Mémoire. 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: Formuler une question Nettoyer un fichier Ajuster un modèle simple 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.
Ce diplôme est académique et entièrement en ligne. Il ne remplace pas une licence d'ordre professionnel, un concours d'État, ni une équivalence ministérielle automatique.
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Data scientists francophones du public et du développement.
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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 |
|---|---|---|
| FR-DA101 | Statistique inférentielle Statistique inférentielle (FR-DA101) is a 6-credit course on Master Science des données appliquée, with 60 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Statistique inférentielle 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.
| 6 · 60 h |
| FR-DA102 | Programmation pour les données Programmation pour les données (FR-DA102) is a 6-credit course on Master Science des données appliquée, with 60 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Programmation pour les 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.
| 6 · 60 h |
| FR-DA103 | Qualité des données Qualité des données (FR-DA103) is a 6-credit course on Master Science des données appliquée, with 60 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Qualité 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.
| 6 · 60 h |
| FR-DA104 | Visualisation responsable Visualisation responsable (FR-DA104) is a 6-credit course on Master Science des données appliquée, with 60 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Visualisation responsable 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.
| 6 · 60 h |
| Code | Course | Credits · hours |
|---|---|---|
| FR-DA201 | Apprentissage supervisé — prudence Apprentissage supervisé — prudence (FR-DA201) is a 6-credit course on Master Science des données appliquée, with 60 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Apprentissage supervisé — prudence 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 24 mois. Teaching language: Français. 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. 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
| 6 · 60 h |
| FR-DA202 | Mémoire Mémoire (FR-DA202) is a 18-credit course on Master Science des données appliquée, with 180 notional learning hours. By the end, students can apply the method of the subject to a defined problem and defend the result, using Mémoire 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.
| 18 · 180 h |