MSE-213: Probability and statistics for materials scienceThe course establishes the concepts of statistical analysis, probability theory, and data analysis. This includes standard statistical tests, correlation analysis and experimental design. It introduces computational statistical methods to analyse large dat ...
DH-406: Machine learning for DHThis course aims to introduce the basic principles of machine learning in the context of the digital humanities. We will cover both supervised and unsupervised learning techniques, and study and implement methods to analyze diverse data types, such as imag ...
BIO-493: Scientific project design in integrative neurosciencesIn this course, students will investigate causal neuronal network mechanisms underlying sensory-guided decision-making in mice. Students will analyse published data to develop integrative neuroscience research projects including the design of new experimen ...
EE-566: Adaptation and learningIn this course, students learn to design and master algorithms and core concepts related to inference and learning from data and the foundations of adaptation and learning theories with applications.
DH-405: Foundations of digital humanitiesThis course introduces the core concepts and methodologies of Digital Humanities, integrating both theoretical and practical perspectives. Students learn to work with large-scale cultural datasets, acquiring the tools and techniques required for their proc ...
CS-423: Distributed information systemsThis course introduces the foundations of information retrieval, data mining and knowledge bases, which constitute the foundations of today's Web-based distributed information systems. ...
FIN-525: Financial big dataThe course introduces modern methods to acquire, clean, and analyze large quantities of financial data efficiently. The second part expands on how to apply these techniques and robust statistics to financial analysis, in particular to intraday data and inv ...
CS-433: Machine learningMachine learning methods 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. ...
BIO-378: Travaux pratiques de physiologie ILe TP de physiologie introduit les approches expérimentales du domaine biomédical, avec les montages de mesure, les capteurs, le conditionnement des signaux, l'acquisition et traitement de données.
Les résultats physiologiques finaux illustrent le contenu ...
BIOENG-519: Methods: omics in biomedical researchHigh-throughput methodologies broadly called Omics allow to characterize the complexity and dynamics of any biological system. This course will provide a general description of different methods related to the Omics field followed by hands-on rotations in ...
BIO-379: Travaux pratiques de physiologie IILe TP de physiologie introduit les approches expérimentales du domaine biomédical, avec les montages de mesure, les capteurs, le conditionnement des signaux, l'acquisition et traitement de données.
Les résultats physiologiques finaux illustrent le contenu ...
DH-412: History and the digitalThe course presents a number of computational approaches & tools that can be used to study history. Drawing on case studies from the history of science & technology, the course also offers students the opportunity to critically reflect on their own practic ...
