CIVIL-459: Deep learning for autonomous vehiclesDeep 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,
MGT-424: Advanced data driven business analyticsThis course aims to provide graduate students a grounding in the methods, theory, mathematics and algorithms needed to apply machine learning techniques to in business analytics domain. The course cov
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 fi
CS-421: Machine learning for behavioral dataComputer environments such as educational games, interactive simulations, and web services provide large amounts of data, which can be analyzed and serve as a basis for adaptation. This course will co
MATH-131: Probability and statisticsLe cours présente les notions de base de la théorie des probabilités et de l'inférence statistique. L'accent est mis sur les concepts principaux ainsi que les méthodes les plus utilisées.
CS-456: Deep reinforcement learningThis course provides an overview and introduces modern methods for reinforcement learning (RL.) The course starts with the fundamentals of RL, such as Q-learning, and delves into commonly used approac
CS-233: Introduction to machine learningMachine 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
