General aims
The application of artificial intelligence -AI- to medicine can contribute to the improvement of population health. This course focuses on artificial intelligence methods programming. It aims to acquire knowledge in the field of artificial intelligence to apply it to the health field by combining algorithmic and modelling knowledge.
Learning objectives
This course is designed for the students to gain knowledge on the following subjects:
- Artificial intelligence programs and tools for health; artificial intelligence algorithms and methods;
- Programming in Python.
Core competencies
Throughout this course the students are expected to acquire the following competencies:
- Knowing how to program in Python;
- Knowing how to implement analyses using artificial intelligence methods using programs in Python;
- Knowing how to interpret the obtained results and understanding their possible limitations.
This C.E.S.U. participates in the training of the Doctoral School of Sciences de la Vie et de la Santé.
In the case where a student who has validated this C.E.S.U. applies for the DESU AI4PH (Artificial Intelligence for Public Health, training officer: Pr Roch Giorgi), or for the Master 2 AI4PH (Artificial Intelligence for Public Health, training officers: De Jean-Charles Dufour, Pr Roch Giorgi), specialization of the Master’s degree in Public Health (training officers: Pr Stéphanie Gentile, Pr Roch Giorgi), the latter would capitalise only those teaching units for which he/she would have obtained a mark ≥ 10 (all individually validated TU are accredited).
Admission requirements
This course is aimed at students and professionals who have completed an M2 course and are carrying out research and/or thesis work on a topic involving artificial intelligence methods for health and are led to programme them.
Language prerequisites
Applicants must demonstrate proficiency in English.
Students whose first language is not English must provide an English certificate with at least the B2 level or equivalent.
Educational organisation
This course is eligible to be entirely taken on-line.
This course is organised in 60 hours: 30 hours of theorical lecturing, and workshops, and 30 hours of supervised student independent work.
The teaching program will include mentoring sessions using Information and Communication Technologies. All the course material, including homework, training exercises, quizzes, self-assessment tests, discussion forums and workshops will be available on the course on-line teaching platform.
Program
The post graduate diploma is composed of 2 teaching modules:
| Schedule | Sheet | Name |
|---|---|---|
| | | Programming fundamentals for health data (INF-PROF) |
| | Artificial intelligence programming (INF-GRAM) |
The main subjects taught are:
- The fundamentals of programming and the main artificial intelligence tools for health;
- Advanced algorithms and methods of artificial intelligence and how to program them using Python.
Exams
The evaluation of each teaching module is done according to its own modalities. Both continuous assessment of knowledge and a final exam will be considered to determine the D.E.S.U. final global grade. In order to pass each teaching module, a minimum grade of 10 out of 20 is required.
In order to obtain the final C.E.S.U. diploma a minimum global grade of 10 out of 20 is required. There is no compensation between teaching modules.
Only one evaluation session is organised per academic year.
Teaching location
Lectures will take place in the multimedia classrooms of the Faculté des sciences médicales et paramédicales of Marseille, France.
Maximum number of students who can register for the C.E.S.U.
The number of students who can take this C.E.S.U. is limited to 8.
