Health

Master's Degree in Epidemiology, Health Data, Biostatistics (EDSB) with a specialization in Data Analysis for Life Sciences

  • ECTS

    60 credits

  • Duration

    1 year

  • Training structure

    School of Pharmacy

  • Language(s) of instruction

    French

Presentation

The proposed course is an evolution of the "Statistics for Life Sciences" course in the "Mathematics" program from the previous period. The Master 1 program will now be shared with the "Epidemiology, Health Data, Biostatistics - Health Data" course, with which there was already significant overlap during the previous period.

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Objectives

Its objective remains to provide students, mainly from health and biology degree programs, with the opportunity to acquire dual expertise in biostatistics.

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Know-how and skills

This dual skill set is particularly sought after in the job market, as shown by the employment rate figures at the end of the program. Our students are real assets to any team, as they have the necessary background in biology/health to master the issues at hand and the skills to analyze data appropriately. This adequate analysis of data in biology/health is a major challenge for research in the coming years, as data is becoming increasingly voluminous and numerous, and errors in its analysis can lead (and have already led in the past) to erroneous or non-reproducible conclusions that discredit the entire research sector. Real expertise in data analysis is therefore essential today in order to answer complex biological questions. This objective is the "DNA" of our training program and will continue to be so for the next period.

In addition, we have updated the course content to enable health and biology students to acquire skills that are increasingly relevant to the biostatistics job market: introduction to the Python language, reinforcement of teaching in machine learning and artificial intelligence. This change is also consistent with the change in specialization, as the health applications of these methods are becoming increasingly numerous (biomarker research, personalized medicine, etc.). We have reinforced our teaching in this area to enable our students (particularly those who do not come from health-related fields) to become aware of the issues inherent in health data.

From a professional perspective, we offer a new case study course unit, introducing project-based learning, which is known for its educational benefits. This course unit is accompanied by an introduction to project management, preparing our students for their future jobs, which often involve working in teams built around projects.

 

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Organization

Knowledge assessment

Program

  • ANALYSIS OF CENSORED DATA

    2.5 credits
  • TEMPORAL STATISTICS

    2.5 credits
  • GENERALIZED LINEAR AND MIXED MODEL

    5 credits
  • Mixed model application & machine learning

    2.5 credits
  • CASE STUDY PART 2

    5 credits
  • MACHINE LEARNING LEVEL 1: APPLICATION TO FORECASTING

    2.5 credits
  • LEVEL 2 DATABASES

    2.5 credits
  • MACHINE LEARNING LEVEL 2

    2.5 credits
  • PLANNED DATA COLLECTION

    2.5 credits
    • CC data collection plan

    • CT data collection plan

  • INDUSTRY STATISTICS

    2.5 credits
  • RESEARCH SEMINARS

    2.5 credits
  • Master's degree internship

    25 credits
    • Internship report

    • Oral exam

  • M2 EDSB internship

    30 credits