Artificial Intelligence for One Health is an accredited Master's programme. AI4OneHealth is a one-year / 60 ECTS credits, Master's degree, entirely taught in English and 100% online. Course materials are hosted on our learning platform. Some classes involve Zoom live sessions.
It is open to well-trained individuals who have successfully completed 4 consecutive years of higher education (equivalent to 240 ECTS) in a relevant field, and who have a good command of the English language.
Students start the AI4OneHealth program with an introductive course including self-evaluations and necessary upgrade courses. Upon completion, students will be awarded a Master Degree from Université Grenoble Alpes and they will also receive the "Professional Qualification in Artificial Intelligence" label from the Multidisciplinary Institute in Artificial Intelligence (MIAI) of Grenoble.
Here is a calendar overview. Please, note that the calendar might change and evolve every year.
Programme
Semester 1
You will study the 4 compulsory core subjects to gain 15 ECTS credits and you will have to choose 4 to 5 elective subjects to make a total of 15 ECTS credits. You will be required to attend Zoom live sessions and study various course materials such as videos, slides, articles and so on. As our programme emphasises practical work, you will be required to submit personal work in the form of reports, code notebooks, and so on. You will also attend online conferences led by AI experts. Some courses involve group work.
Assessments vary by class and may involve personal works, online quizzes, oral presentations or group projects.
Some elective courses have prerequisites such as a certain level of programming proficiency in specific coding languages or other requirements.
| Core & Elective Subjects | ECTS |
|---|---|
| Core Subjects (15 ECTS) | |
| MCXA0044 Introduction to AI for Health | 3 |
| Winterschool "The challenges of IA in for diseases" | 6 |
| MCXA0041 Ethical and societal aspects of Artificial Intelligence | 3 |
| MCXA0032 Neural network modelling AI for Health Applications | 3 |
| Elective Subjects (15 ECTS) | |
| MCXA0029 Data management technologies, policies and ethics | 3 |
| MCXA0034 Machine learning and Deep learning for health | 3 |
| MCXA0031 Artificial intelligence for OMICS | 6 |
| MCXA0042 Application of AI for Healthcare | 3 |
| MCXA0043 Internet of things and AI for Health | 3 |
| MCXA0046 AI in health environnement | 3 |
| MCXA0047 Medical text mining | 3 |
| MCXA0068 Computer Vision for Medical imaging | 3 |
Semester 2
| Path | ECTS |
|---|---|
| Internship M2 or project | 30 |
| OR | |
| Internship M2 | 27 |
| Collaborative project | 3 |
| OR | |
| Internship M2 | 24 |
| Intensive School Planned Health (GS@UGA) | 6 |
Winterschool "The challenges of IA in for diseases" :
The school is taught during the winter season, typically at the end of January. It usually involves two intensive weeks including live Zoom sessions and a group project. The subject varies from year to year but usually involves AI and its applications in healthcare. Students are assessed through an oral group presentation.
Here is an example of last year's planning.
Internship
You will need to complete a 5 months internship either in the private or in the public sector, in an academic or industrial laboratory. The subject must be approved and all administrative procedures must be completed before you start the internship. You will need find the internship yourself and the subject is to be determined with the staff member that will supervise you. The internship is assessed through a master’s thesis written in English in the form of a scientific article. An oral defence will be held at the end of the internship.