This course will train doctoral students to use bioinformatic tools to analyse amplicon and metagenomic sequences. In addition, we will also touch upon meta-transcriptomics and meta-proteomics. ...
Machine learning and data analysis are becoming increasingly central in sciences including physics. In this course, fundamental principles and methods of machine learning will be introduced and practised. ...
Biology is becoming more and more a data science, as illustrated by the explosion of available genome sequences. This course aims to show how we can make sense of such data and harness it in order to understand biological processes in a quantitative way. ...
La Physique Générale I (avancée) couvre la mécanique du point et du solide indéformable. Apprendre la mécanique, c'est apprendre à mettre sous forme mathématique un phénomène physique, en modélisant la situation et appliquant les lois de la physique. ...
A first graduate course in algorithms, this course assumes minimal background, but moves rapidly. The objective is to learn the main techniques of algorithm analysis and design, while building a repertory of basic algorithmic solutions to problems in many ...
Deep Learning (DL) is the subset of Machine learning reshaping the future of transportation and mobility. In this class, we will show how DL can be used to teach autonomous vehicles to detect objects, make predictions, and make decisions. (Fun fact: this s ...
This course will take place from 3rd to 7th June 2024.It will introduce the workflows and techniques that are used for the analysis of bulk and single cell RNA-seq data. It will empower students to understand and analyze their own data. ...
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 literature on nonlinear signal processing has exploded, and it becomes more and more difficult to identify the most useful approaches for specific contexts. This course presents promising developments for the practical application of nonlinear signal m ...