The Programme Specification for the 2022 intake onwards sets out five objectives (PO1–PO5) and six outcome groups (PLO1–PLO6, 13 criteria). Students follow their own intake documents. The 2026 update applies once formally issued.
Foreign-language exit standard: level 4/6 of the Vietnamese framework (≈ B2). The full wording of the outcomes, the objective–outcome matrix and the course–outcome matrix are in the programme documents (Documents by cohort).
One credit equals 2 ECTS (University conversion rule), 120 ECTS for the whole programme. The foreign-language course is a prerequisite and is not counted in the GPA.
The bar illustrates track 1; the table gives the allocation for all three tracks.
| Track | General | Core (compulsory) | Electives | Research / Internship | Thesis / Project | Total |
|---|---|---|---|---|---|---|
| Track 1 — research | 3 | 16 | 12 | 14 (research project) | 15 (thesis) → thesis block 29 cr. | 60 |
| Track 2 — applied, with thesis | 3 | 16 | 28 | — | 13 (thesis) | 60 |
| Track 3 — applied, internship + project | 3 | 12 | 32 | 6 (internship) | 7 (graduation project) | 60 |
Track 1 requires a scientific publication or an accepted intellectual-property application before the defence; tracks 2 and 3 earn bonus marks for a publication. Details: Thesis and Graduation.
Specialist courses carry four credits (three theory and one practical), equivalent to 8 ECTS. Check the curriculum for your intake for the applicable list. English titles follow the course syllabi.
Philosophy (3 credits). Foreign Language is a prerequisite course: students must reach level 4/6; it is not counted in the GPA.
| Code | Course | Credits |
|---|---|---|
| MTH058 | Advanced Artificial Intelligence | 4 |
| MTH003 | Advanced Database Systems | 4 |
| MTH080 | Advanced Machine Learning | 4 |
| MTH074 | Mathematical Methods in Computer Science and Algorithms | 4 |
| MTH090 | Mathematics for Data Science | 4 |
| MTH010 | Distributed Systems | 4 |
| MTH045 | Data Analytics Science | 4 |
| MNC | Scientific Research Methodology (compulsory for tracks 1 and 2) | 4 |
Management Information Systems
| Code | Course | Credits |
|---|---|---|
| MTH107 | Digital Commerce | 4 |
| MTH099 | Advanced Information Systems Analysis and Design | 4 |
| MTH015 | Mobile Information Systems | 4 |
| MTH042 | Safety and Security in Information Systems | 4 |
| MTH041 | Decision Support Systems | 4 |
Intelligent Data Analytics
| Code | Course | Credits |
|---|---|---|
| MTH036 | Advanced Business Intelligence Applications | 4 |
| MTH071 | Data Analysis Models | 4 |
| MTH072 | Data Visualization | 4 |
| MTH055 | Big Data Mining | 4 |
Free electives
| Code | Course | Credits |
|---|---|---|
| MTH108 | Digital Transformation | 4 |
| MTH109 | Cloud Services | 4 |
| MTH035 | Information Retrieval Systems | 4 |
| MTH075 | Information Systems Project Management | 4 |
| MTH038 | New Technologies in Information Systems Development | 4 |
| MTH089 | Advanced Text Mining | 4 |
| MTH078 | Recommender Systems | 4 |
The framework allows the remaining core courses, the two specialisation groups, the free-elective group and electives of the Faculty's Master of Computer Science and Master of Artificial Intelligence programmes.
MTH106 Internship: 6 credits of practice in a company, research institute or applied unit, linked to the graduation project.
Track 1: Research project (14 cr.) + Thesis (15 cr.). Track 2: Thesis (13 cr.). Track 3: Graduation project (7 cr.). See Thesis and Graduation.
Detailed syllabi (objectives, content, assessment, reading) are published by the Faculty with the curriculum framework on the Faculty website (Vietnamese).
The plan below is a model. Follow the course schedule for your intake to stay on track, as a course usually runs only once per cohort.
Advanced Database Systems, Distributed Systems, Advanced AI and an elective. Register a track.
Scientific Research Methodology, Advanced BI Applications, IS Project Management, Advanced Systems Analysis and Design. Track 1 starts its research project.
Decision Support Systems, IS Security, Data Analytics Science, Advanced Text Mining, Philosophy. Tracks 2 and 3 register their topic.
Data Analysis Models, Cloud Services and electives; thesis (tracks 1, 2) or internship and graduation project (track 3); defence.
Key milestones from the Student Handbook: track registration about three months after enrolment; track 1 registers its topic earlier (months 4–6 of year one) because the research phase is longer; tracks 2 and 3 register at the end of year one; defence at the end of year two. Your cohort's exact dates are in the Student Handbook.
Courses combine lectures, practical work, seminars, assignments and group projects linked to research or applications. Materials and submissions are managed through the Faculty learning system.
Each course is assessed by coursework and a final assessment on a 10-point scale, with weights stated by the lecturer in the syllabus. Theses and projects are graded by a committee under University procedure. Exams, appeals and retakes follow the master's training regulations.
Entry level 3/6, exit level 4/6 of the Vietnamese framework or an equivalent certificate. The list of recognised certificates and exemptions follows the announcements of the Office of Graduate Studies.
Each intake has its own curriculum framework issued by the University. Open the PDF for your intake (documents are in Vietnamese); amending decisions apply to the intakes they name.
The programme applies from the 2022 intake under Decision 2449/QĐ-KHTN of 16/12/2022. MTH075 increased to four credits from the 2023 intake (Decision 1634/QĐ-KHTN); the framework was restructured in 2024. Students follow their own intake documents.
The Vietnamese–French double degree with Université Claude Bernard Lyon 1 is a separate programme, with admissions paused since 2021.