PHYS-467: Machine learning for physicistsMachine 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. ...
CH-457: AI for chemistryThe AI for Chemistry course will focus on teaching students how to use machine learning algorithms and techniques to analyze and make predictions about chemical data. The course will cover topics such as the basics of machine learning, common algorithms an ...
ENG-209: Data science pour ingénieurs avec PythonCe cours propose une immersion progressive et complète dans le domaine de la Data Science à travers le langage Python. Il guide les étudiants depuis la manipulation de données brutes jusqu'à la modélisation et l'extraction de connaissances utiles à partir ...
CS-422: Database systemsThis course is intended for students who want to understand modern large-scale data analysis systems and database systems. It covers a wide range of topics and technologies, and will prepare students to be able to build such systems as well as read and und ...
HUM-485: Data in context: Critical Data Studies ILe cours "Critical Data Studies" s'inscrit dans la nouvelle offre d'enseignements TILT qui propose de croiser des savoirs provenant des SHS et des sciences de l'ingénieur afin d'aborder des thématiques complexes qui nécessitent une méthodologie interdiscip ...
AR-680: Urbanism of Hope. 16th IFoU Conference.In a context of global crisis, the 16th IFoU conference focuses on attempts, approaches, and solutions on local level. To what extend are they able to reduce the impact of environmental disasters, to improve resiliency and social integration, to overcome f ...
BIO-604: ORPER summer schoolThis summer school will provide PhD students knowledge on the different practices that they can adopt from the beginning of their research journey onwards, to improve the quality, transparency, shareability and reproducibility of their work. ...
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 ...
BIOENG-450: In silico neuroscience"In silico Neuroscience" introduces students to a synthesis of modern neuroscience and state-of-the-art data management, modelling and computing technologies. ...
MGT-448: Statistical inference and machine learningThis course aims to provide graduate students a thorough grounding in the methods, theory, mathematics and algorithms needed to do research and applications in machine learning. The course covers topics from machine learning, classical statistics, and data ...
CS-233(a): Introduction to machine learning (BA3)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. ...
AR-302(ai): Studio BA6 (Shahbazi)The studio of Shirana Shahbazi asks how we can imagine, reflect and depict the intangible qualities of the city and spaces. It is an attempt to shift the centre of attention and rethink value. We will create images of the in-between and its hidden qualitie ...
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. ...
AR-402(ai): Studio MA2 (Shahbazi)The studio of Shirana Shahbazi asks how we can imagine, reflect and depict the intangible qualities of the city and spaces. It is an attempt to shift the centre of attention and rethink value. We will create images of the in-between and its hidden qualitie ...
