CS-401: Applied data analysisThis 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 dat
AR-604: Introduction to research IIThis course is an introduction to the methodological issues of scientific research. The objective is to help doctoral students conduct a scientifically robust research.
MGT-644: Conducting Qualitative ResearchThis workshop will expose you to a combination of readings, discussions, and hands-on exercises aimed at cementing your
understanding of, and ability to conduct qualitative research - especially gathe
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 imple
CIVIL-349: Traffic engineeringIntroduce the major elements of transportation systems and traffic engineering: develop analytical and technical skills in applying the fundamentals of the transport field; understand the key concepts
HUM-403: Experimental cognitive psychology IThe media frequently report on trendy studies that have been conducted in experimental cognitive psychology, and which inform the public on "human functioning" and its causes. We teach students basic
ENV-596: Design projectMise en pratique des connaissances acquises dans un projet proposé par un bureau d'ingénieur, une administration ou un laboratoire affilié à SIE. Projet avec une orientation d'ingénierie ou de recherc
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.
CS-448: Sublinear algorithms for big data analysisIn this course we will define rigorous mathematical models for computing on large datasets, cover main algorithmic techniques that have been developed for sublinear (e.g. faster than linear time) data
BIO-614: Practical - Antanasijevic LabThe students will learn:
- how to handle viral protein antigens and antibody samples
- how to assemble and purify immune complexes using liquid chromatography
- how to image them on an electron
PENS-220: Carving natural stonesSur la base d'un cahier des charges, concevoir de manière interdisciplinaire un projet de structure, principalement en pierre de taille, esthétique et fonctionnel (abri thermique), faisant usage de pl
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, analy