The course provides an introduction to econometrics for economics and financial applications. The objective is to learn how to make valid (i.e., causal) inference from economic and social data. ...
Ce cours présente les principes fondamentaux à l'œuvre dans les organismes vivants. Autant que possible, l'accent est mis sur les contributions de l'Informatique aux progrès des Sciences de la Vie. ...
Students will learn the core concepts and techniques of network analysis with emphasis on causal inference. Theory and
application will be balanced, with students working directly with network data throughout the course. ...
This course integrates knowledge in basic, systems, clinical and computational neuroscience, and engineering with the goal of translating this integrated knowledge into the development of novel methods, technology for the clinical application for patients ...
This course teaches how to apply exploratory spatial data analysis to health information. Teaching focuses on the role of GIS and spatial statistics in spatial epidemiology. It proposes a context to investigate the relationship between health, quality of l ...
This course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the data science world (pandas, scikit-learn, Spark, etc.) ...
Sitting at the crossroad of organic chemistry and medicine, this course outlines how an initial hit compound transitions into a lead candidate, and ultimately a drug, in the modern drug discovery world.Note: the course is held only during 2nd half of spr ...
Information-theoretic methods and their application to secrecy & privacy. Perfect information-theoretic secrecy. Randomness extraction & privacy amplification. Secret key generation from common randomness. Measures of information leakage incl. differential ...