Master in Public Health - Course: Statistics, Modeling and Health Data Sciences
24 monthsProgramme duration
353 EURTuition Fee/year
SepStarting Month
Programme overview
Main Subject
Health/Healthcare
Degree
MPH
Study Level
Masters
Study Mode
On Campus
Statistics, a discipline at the heart of biomedical research, structures the methodology of biological, clinical or epidemiological studies. Historically based on mathematical and statistical principles applied to health data, it has gradually integrated methods from information technologies to respond to the methodological issues raised by increasingly rich and complex data.
In particular, the computerization of the health system (National Health Data System, Hospital data warehouses, Health Data Hub, etc.) and the creation of large-scale biological databases (“omics” disciplines simultaneously studying thousands of variables) have enabled the development of specific analysis tools to respond to these new challenges relating to Massive Health Data ( Health Big Data ). Data Science, represented by the profession of data scientist, thus integrates modern statistical tools with algorithms derived from automatic learning methods ( machine learning and artificial intelligence) and data mining ( data mining). It offers a constantly expanding range of tools to respond to ever more specific problems.
These growing disciplines, however, require the integration of skills in statistics and computer science, while offering many scientific and professional perspectives in various fields: clinical research, epidemiology, medico-economic analyses, pharmaceutical industry, etc.
Programme overview
Main Subject
Health/Healthcare
Degree
MPH
Study Level
Masters
Study Mode
On Campus
Statistics, a discipline at the heart of biomedical research, structures the methodology of biological, clinical or epidemiological studies. Historically based on mathematical and statistical principles applied to health data, it has gradually integrated methods from information technologies to respond to the methodological issues raised by increasingly rich and complex data.
In particular, the computerization of the health system (National Health Data System, Hospital data warehouses, Health Data Hub, etc.) and the creation of large-scale biological databases (“omics” disciplines simultaneously studying thousands of variables) have enabled the development of specific analysis tools to respond to these new challenges relating to Massive Health Data ( Health Big Data ). Data Science, represented by the profession of data scientist, thus integrates modern statistical tools with algorithms derived from automatic learning methods ( machine learning and artificial intelligence) and data mining ( data mining). It offers a constantly expanding range of tools to respond to ever more specific problems.
These growing disciplines, however, require the integration of skills in statistics and computer science, while offering many scientific and professional perspectives in various fields: clinical research, epidemiology, medico-economic analyses, pharmaceutical industry, etc.
Admission Requirements
- to students in initial training who have validated a first year of Master in Public Health with a strong component in statistics or mathematics or equivalent training (for example Cesam inter-university diploma);
- to adults in continuing education with professional experience related to the specialty of the diploma, subject to validation of the necessary professional skills.
Applications will be examined by a teaching committee issuing registration authorizations.
Tuition fees
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International
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