Master's 1 in Epidemiology, Health Data, and Biostatistics (EDSB)

The EDSB Master 1 program serves as the common foundation for training in epidemiology, biostatistics, and data analysis as applied to health and the life sciences. It aims to provide students with the necessary foundations to understand, organize, and analyze data from a variety of contexts, including clinical research, epidemiological studies, public health, biology, and the life sciences.

The curriculum covers, among other topics, inferential statistics, the general linear model, quantitative epidemiology, randomized clinical trials, data mining, databases, and the analysis of omics data. The program also includes comprehensive hands-on training in the main programming languages used in data analysis—including R, SAS, and Python—as well as an introduction to big data and artificial intelligence in healthcare.

The goal is to train students who are not only able to apply statistical methods, but above all capable of answering a scientific question, because they will have understood the underlying assumptions, learned to select the appropriate methods for analyzing the data, and learned to correctly interpret the results and critically evaluate the analyses performed.

The M1 program thus provides a common methodological foundation before students specialize in the M2 program in health data analysis or data science applied to the life sciences. A two-month introductory research internship allows students to apply the knowledge they have acquired to a real-world research problem.