Recommender Systems: Behind the Screen

via edX

Overview

Delve into the world of Recommender Systems: Behind the Screen, a comprehensive course meticulously designed by IVADO and HEC Montréal. This enlightening education journey, hosted in Montreal, offers a deep dive into the methodologies and practices behind recommender systems. These systems play a pivotal role in shaping personalized online experiences by analyzing patterns in user behavior to suggest items like books, movies, recipes, and even potential connections.

This offering, developed in partnership with industry and academic luminaries worldwide, is structured as an introductory MOOC in the domain of recommender systems. The curriculum outlines essential topics such as machine learning applications, evaluation methods, advanced modeling, contextual bandits, ranking methods, and addressing fairness and discrimination within these systems.

Targeting industry professionals and academics with foundational knowledge in mathematics and programming (Python preferred), this course also caters to graduate students in science and engineering domains unfamiliar with machine learning and recommender systems. Furthermore, anyone with a keen interest in AI will find valuable insights and applications within the content presented.

Expect a six-week journey through the intricacies of recommender systems, featuring segmented content for flexible pacing, comprehensive quizzes for each section, hands-on algorithm tutorials, and an extra practice module for verified certificate holders.

This unique educational experience is made possible through the collaboration of IVADO, HEC Montréal, and Université de Montréal, institutions recognized for their contributions to digital intelligence and internationally acclaimed management education and research, respectively.

Join us on this special journey into the realm of AI and recommender systems, brought to you by leaders in digital intelligence and higher education. Enroll in Recommender Systems: Behind the Screen on edX, under the categories of Machine Learning, Mathematics, Programming, and Recommender Systems Courses.