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 ...
Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented. ...
The "Introduction to Applied Data Science" (I2ADS) course is aimed at students of all levels to train them in the core computer science software stack and techniques forming the pillars of open & reproducible science.
Registration in student portal & at ht ...
This course aims at giving a broad overview of Bayesian inference, highlighting how the basic Bayesian paradigm proceeds, and the various methods that can be used to deal with the computational issues that plague it. This course represents a 70-30 split of ...
Introduction to systems engineering using the classical V-model. Topics include stakeholder analysis, requirements definition, concept selection, design definition and optimization, system integration and verification and validation. This class is part of ...
An overview course intended for scientists and engineers who need to use statistical methods as part of their research, who have already attended a course at the second-year EPFL undergraduate level, and need revision and deepening of their knowledge at a ...
"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies. ...
Statistical learning theory for supervised learning and generalization in PAC and online models (VC theory, MDL/SRM, covering numbers, Radamacher Averages, boosting, compression, stability and connection with strong convexity in Banch spaces); Computationa ...