ECTS
60 credits
Duration
1 year
Training structure
Faculty of Pharmacy
Language(s) of instruction
French
Presentation
The proposed course is an evolution of the course "Statistics for Life Sciences" of the mention "Mathematics" of the previous period. The Master 1 becomes common with the course "Epidemiology, health data, biostatistics - Health data" with which the mutualization was already very important during the previous period.
Objectives
Its objective remains to provide students coming mainly from health and biology bachelor's degrees to acquire a double competence in biostatistics.
Know-how and skills
This dual competence is particularly sought after on the job market, as shown by the insertion rate figures at the end of the program. Our students are real assets in a team since they have the necessary culture in biology/health to master the problem of interest and the competence to analyze the data adequately. This adequate analysis of data in biology/health is a major issue for research in the years to come because the data are increasingly voluminous and numerous and errors in their analysis can lead (and have already led in the past) to erroneous or non-reproducible conclusions that discredit the entire research field. A real expertise in data analysis is therefore essential today to answer complex biological questions. This objective is the "DNA" of our training and will continue for the next period.
In addition, we have developed the content of the training to enable health and biology students to acquire skills that are ever closer to the job market in biostatistics: introduction of the Python language, reinforcement of lessons in Machine Learning and artificial intelligence. This evolution is also consistent with the change of mention because the health applications of these methods are increasingly numerous (biomarker research, personalized medicine, etc.). We have strengthened the teaching on this point, allowing our students (especially those who do not come from health fields) to become aware of the problems inherent in health data.
From a professional point of view, we are proposing a new case study course, allowing us to introduce project-based learning, the pedagogical virtues of which we know. This course is accompanied by an awareness of project management, preparing our students for their future jobs, which often involve working in teams built around projects.
Organization
Knowledge control
Program
ANALYSIS OF CENSORED DATA
2.5 creditsTIME STATISTICS
2.5 creditsGENERALIZED AND MIXED LINEAR MODEL
5 creditsMixed model & machine learning application
2.5 creditsCASE STUDY PART 2
5 creditsMACHINE LEARNING LEVEL 1: APPLICATION TO PROGNOSIS
2.5 creditsDATABASE LEVEL 2
2.5 creditsMACHINE LEARNING LEVEL 2
2.5 creditsPLANNED DATA COLLECTION
2.5 creditsSTATISTICS FOR INDUSTRY
2.5 creditsRESEARCH SEMINARS
2.5 credits
Master 2 internship
25 creditsM2 EDSB internship
30 credits