BIOENG-456: Controlling behavior in animals and robotsStudents will acquire an integrative view on biological and artificial algorithms for controlling autonomous behaviors in animals and robots. Students will synthesize and apply this knowledge in oral presentations and exercises.
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.
CS-411: Digital educationThis course addresses the relationship between specific technological features and the learners' cognitive processes. It also covers the methods and results of empirical studies on this topic: do student actually learn due to technologies?
MICRO-452: Basics of mobile roboticsThe course teaches the basics of autonomous mobile robots. Both hardware (energy, locomotion, sensors) and software (signal processing, control, localization, trajectory planning, high-level control) will be tackled. The students will apply the knowledge to program and control a real mobile robot.
MSE-212: Biology for engineersLe cours est une introduction aux sciences de la vie en tant que domaine pluridisciplinaire ayant de multiples connexions avec l'ingénierie des matériaux. Il permettra aux étudiants de trouver dans la biologie une inspiration lors des leur activités dans le domaine des matérieaux.
DH-405: Foundations of digital humanitiesThis course gives an introduction to the fundamental concepts and methods of the Digital Humanities, both from a theoretical and applied point of view. The course introduces the Digital Humanities circle of processing and interpretation, from data acquisition to new understandings.
CS-503: Visual intelligence : machines and mindsThe course will discuss classic material as well as recent advances in computer vision and machine learning relevant to processing visual data with a primary focus on embodied intelligence and vision for active agents.
CS-456: Artificial neural networks/reinforcement learningSince 2010 approaches in deep learning have revolutionized fields as diverse as computer vision, machine learning, or artificial intelligence. This course gives a systematic introduction into influential models of deep artificial neural networks, with a focus on Reinforcement Learning.
CS-119(c): Information, Computation, CommunicationL'objectif de ce cours est d'introduire les étudiants à la pensée algorithmique, de les familiariser avec les fondamentaux de l'Informatique et de développer une première compétence en programmation (langage C++).
COM-490: Large-scale data science for real-world dataThis hands-on course teaches the tools & methods used by data scientists, from researching solutions to scaling up
prototypes to Spark clusters. It exposes the students to the entire data science pipeline, from data acquisition to
extracting valuable insights applied to real-world problems.