The overall structure of the programme is based on a proven complementary approach to Internet-based learning, combining:
- courses delivered synchronously online (NetConferences),
- online learning materials accessible via a distance learning platform and viewable through any type of web browser (the Digital Learning Environment and Distance Learning Platform of Aix-Marseille University),
- pedagogical support for learners, including asynchronous tutoring (e-mail, forum) and synchronous tutoring (use of a dedicated audio-video NetConference tool via standard Internet-connected PCs).
Please note that:
- NetConferences are held live and are not recorded.
- Attendance at NetConferences is mandatory in order to validate the teaching units that make up this programme.
- Students must ensure that they have the required equipment (speakers, headphones, or—strongly recommended—a headset with microphone) and an Internet connection with sufficient bandwidth to participate throughout the programme (minimum stable bandwidth of 128 Kbps).
- The general schedule, including NetConferences, can be accessed via the “Direct link to…” section on the main page describing this Master’s programme.
Semester and year validation
The assessment procedures for this course comply with the knowledge assessment regulations in force at the Faculty of Medical and Paramedical Sciences of Marseille.
In Master 2 (M2), examinations take place during a single examination session.
The assessment of each Teaching Unit (UE) requires passing a written examination, an oral examination, and/or the completion of various assignments and/or the writing and presentation of a thesis/dissertation.
Internships are assessed through the writing and oral presentation of an internship report.
The semester average is calculated as the weighted average of the Blocks of Knowledge and Skills (BCC), weighted by the ECTS credits of the Teaching Units that compose them.
The assessment procedures for this course comply with the knowledge assessment regulations in force at the Faculty of Medical and Paramedical Sciences of Marseille.
In Master 2 (M2): validation of the academic year requires obtaining an average of at least 10/20 in each BCC.
Pedagogical support tools
Webinars
Conferences are organised in the form of Webinars during which guest speakers present their work. These may be research papers, methodological papers with practical applications, or teaching notes.
Thes series of Webinars is organised in the field of Quantitative Methods and Medical Information Processing (QuanTIM). The presentations made during the QuanTIM Webinars are related to methodological research or to more pedagogical aspects in biostatistics, econometrics, methods for clinical and epidemiological research, biomedical informatics, e-health, information and communication technologies, artificial intelligence,...
Webinars can be in english (ENG) or in french (FR) language. The webinars of the AI4PH specialization are those in english.
An individual assessment, in the form of MCQs, is carried out at the end of each webinar.
The speakers' presentations are recorded, formatted and edited in a format suitable for off-line viewing. These videos and their associated resources are then made available on the SESSTIM - Webinars.
Tutoring
In the majority of the TU of this training, students benefit from distance tutoring. Our tutors are under the direct supervision of the teachers and carry out their role in accordance with our tutoring charter.
Repeating the M2
Repeating the M2 is not allowed, according to the rules of Aix-Marseille University. In exceptional cases, a derogation may be granted after consulting the pedagogical committee.
Overview of the programme
The Master’s programme consists of two semesters and represents a total of 60 credits.
Each semester is divided into Blocks of Knowledge and Skills (BCC), which are themselves broken down into Teaching Units (UE).
In Master 2 (M2), the BCCs from the two semesters are independent.
The M2 learning agreement is worth 60 ECTS credits.
Teaching Units
Master 2 - Semester 3
The learning contract is composed of 6 mandatory teaching units (TU) regrouped in knowledge and skills blocks (BCC).
The number of ECTS credit is 2 for the TU INF-PROF, 4 for the TU INF-GRAM, and 6 for the TU PHS-PRIM, CHA-AIPH, MET-MALE.
BCC : Innovative applications in public health and artificial intelligence
| Name of the Teaching Unit | Descriptive sheet | Schedule |
|---|---|---|
| PHS-PRIM : Principles and methods of public health sciences | 📄 | 📅 |
| Methods of machine learning (MET-MALE) | 📄 | 📅 |
BCC : Development and applications of programming for digital public health
| Name of the Teaching Unit | Descriptive sheet | Schedule |
|---|---|---|
| INF-PROF : Programming fundamentals for health data | 📄 | 📅 |
| INF-GRAM : Artificial intelligence programming | 📄 | 📅 |
BCC : Integrating artificial intelligence into public health for communication and professional transformation
| Name of the Teaching Unit | Descriptive sheet | Schedule |
|---|---|---|
| CHA-AIPH : Artificial intelligence challenges for public health | 📄 | 📅 |
| DAT-ORES : Open and reproductible science | 📄 | 📅 |
Master 2 - Semester 4
The learning contract is composed of 3 mandatory teaching units (TU) and an internship of at least 5 months.
Each TU has a value of 2 ECTS credits and the internship has a value of 24 ECTS credits.
BCC : Advanced analysis of digital data and perceived health in public health
| Name of the Teaching Unit | Descriptive sheet | Schedule |
|---|---|---|
| PHS-PHRM : Patient’s perceptual health measurement and narrative-based medicine | 📄 | 📅 |
| PHS-SNET : Social network analyses for public health issues | 📄 | 📅 |
| MET-NLPF : Fundamentals of natural language processing | 📄 | 📅 |
BCC : Conducting, communicating and promoting scientific research
| Name of the Teaching Unit |
|---|
| End-of-programme internship |
Full-time internship in a laboratory (minimum duration of 5 months) with the writing of a thesis and an oral defense. The internship may take place in any research laboratory subject to the suitability of the internship subject with the student’s training and the agreement of the training officers (for information only, list of work placements where AI4PH students have been accepted).
